Tableau for Data Analysis and Business Intelligence

1. Intro of Course: Hello, everyone. So welcome to the course, tabu for data analysis and visualization. For those who don't know me, my name is Adte and I'm a BS specialist, working in one of the big four firm in India and have around five year experience working in various client related to healthcare, retail domain. So what I thought was to make a course that not only focus upon tabu, but also focus upon how to solve a business problem using tabau. So whether you are a healthcare professional or a data analyst or just curious about the power of data visualization, you are in the right place. So in this particular course, we will deep dive into the world of healthcare analytics using taboo to transform our complex data into insightful dashboard. You will learn how to analyze key metric, identify trends and make data driven decision, and that can improve patient care and operational efficiency. Throughout this course, you will learn how to import and prepare data for analysis, how to create dynamic dashboards, that visualizes critical health metrics, use interactive features that allow user to explore the data on their own, and most importantly, telling a compelling story from your data. By the end of this course, you will have the skills to build impactful dashboard that not only highlight the insight but also drive meaningful change in healthcare setting. So let's get started. Enroll now. And unlock the full potential of the healthcare data with Tableau. Together, we'll make a data visualization an essential part of improving healthcare analytics. So see you in the course. 2. Introduction to Tableau & Products: Ryman. So welcome to the course. So let us just start things off with the introduction of tabu first and let us understand why do we need tabu or BI in the first place, right? So BI means business intelligence. Okay. So the thing is, let me just take an example example. So nowadays, we are wearing smartwatches, right? And whether we are wearing Apple watches or Samsung watches or Pixel watches, we can track our daily activity record. We can track the heart rate, we can track the blood of CN level, right, and we can also track the activity we are doing. So data known as the key performance indicator. So the same thing happens like whenever you're creating a dashboard or something using tabu. So you have to identify in the business you are working with, what are the key performance syndicator that you can track upon. Okay, so let me just take an example. So if will just go to my Apple watch app. So what I can do is I can just go to my health activity. So I wear the watch on 20 in October. So this is the recent activity that I've done. So you can see, I have various KPI that Apple Watch is measuring for me. That is how many moment I have taken moment I've done. How many moment I have done, how many exercise I have done, and what is the standing hours. There are also KPI related to it, target is like 660 kilocalorie, I have to complete, I have to move, but I've only done 608. The excise I have surpassed 30 minutes is the target, and I have surpassed it to 70 in minutes I have excise in a dead day. 12 hours it is matting the target, right? So are some of the KPIs which I'm measuring to keep my personal life a healthy lifestyle. Okay. The same thing can apply to different businesses. So for example, if you're working uh a movie business. So in movie business, you are tracking how many movie is doing good or how many movies are doing bad. And what is the retention rate of people, those are going to the theater for watching movies and those are not watching movies. And what are the reason associated with it, right? So if you want to answer these type of questions, so the thing is, you have the data. The thing is how you can utilize that data. To have some meaningful insight and perform and present to the stakeholders, right. So that what BI means. So BI means you can see decision making speed up using data for a better understanding of business, KPI response. So I've wristed down some of the applications of business teigens. So now moving forward to the Tableau products that we have in market today. So the first product that tabu have is tabu Public. So I just opened tabu Public. So TabuPublic is like a freely available platform for any users can access to it and user can download it for free, and people can post their work online here. So people can also take inspiration from the dashboard that is already created and can make KPL level dashboard or Infographic level dashboard using the inspiration or can also download data like if they provide and you can create this kind of dashboard, right? The second tool that comes in hand is Tablo dekhtop. Okay. So Taboo dektop is like the paid version. So the thing is, you can have a 14 days trial, like if you're starting the paid version, what is the difference between Taboo dektop and Taboo Mobile Taboo Dextop and Tableu public is? In the Taboo Dktop you get an access to about 64 plus data sources you can connect to. Plus, you can also save your workbook offline. But in 2024 version, Taboo public has also announced that you can save the workbook offline now, so one limitation is less now in Taboo Dextop and Taboo public. Then moving forward, once you have developed your dashboard, the thing is you have to publish it somewhere, right? So there are two options available. One is tabu Cloud and one is tabu server. Okay. So tabu server and tabu Cloud, the difference is in tabu server, you can manage your own resources. But in tabu Cloud, all the resources will managed by the Tablo team itself. Okay. And then the other tool comes is tabu prep. Suppose you have various dataset coming with you and you have suppose five different kind of dataset, and you have to do some kind of transformation and cleaning operation. So that time you use TabuPrep. Okay. Then comes Taboo Mobile. Tabomil is the mobile application that interact with visualization on Taboo Server or Tabuloud side. Okay. I hope you are aware of this product now and you've got a little bit idea. And the new thing is you have also got TabuPuls which is available on tabu Cloud package as of now, So let me just give you an overview of tabu pulse. So this is a new platform kind of thing that tabu has offered, and it is included in the tabu Cloud package. So the thing is like, suppose you have prepared a data model. Okay. So data modeling is one of the essential thing that you will do, you will see in this course, how to create a data model from yourself. So once you've created a data model, what you can do is you can ask AI to create a Kp level visual for you or can generate some kind of insight for you. You can ask some kind of quotients with Tableau pulse, and they will generate some kind of visualization that is best suited for the data, and they can give you the analysis. Thing is you can also do some tweaks and turns in tabu pulse, to make your analysis more crisp and more insightful. In this particular course, there's no scope, we'll be not covering tabu pulse in detail, but just wanted to give you an overview, what are the different products that tableau offer. So in this particular course, our main focus will be related to the Tableau dektop and how we can create the visualization using various different kind of data sources and also solve business problem with it. Before de diving into next video and see how to install tabu dektop in a system, just wanted to tell you about some other tools that are other than tabu that are also in the market. The competitor, you can say. So you can see Power BI click or some other competitors, which is with Tableau. But according to the 2024, the survey, which has taken by different companies and analysts. So tableau is one of the leading BI tool. So you are in the right place. Like we're learning your journey, starting your journey with tabu. So you're at the right space. So the thing is, if you learn one tool, the other tool, you can learn it easy. Only thing is the business problem, how to solve, that is necessary, and that is the essence of this course. See you in the next video where we'll install Tableau in your system and then we'll start with the tableau interface thing. 3. Setting-up Tableau: So welcome back. So let us see how to install Tablo Public or Taboo Dextop in our system. So you can also take 14 days trial of Taboo Dektop and you can take up this course and you can try some of the features that are available in tabu Dektop. Or you can also work with TabuPublic because most of the features are available in tabu public. Only the limitations are some features or some kind of data sources options are not available. But will show you both things you can download. So what you can do is just type in your Google Tablo public, go to Table public site, and you can see an option for Create and you can click on Download Taboo DextoPublic edition. Click on that. Fill your information and click on download the app. So once you will click on all the information, you will see a public Installer system. So once you open the app in the Mac if you are working on so you can see an option for taboo dot package file. But if you're in a Windows system, you will get a taboo dot EXE file. Okay. So double click on your EXE file if you're on Windows. So you'll get a public setup like this, same as in Windows. So you can just click on Continue and English language Continue, agree and click on Install. Okay. So it will just install it in your system. So you can just give the password. So if it is asking in your system, it will install this, that will be public addition for me. Okay. So the same thing, you have to do it for the other thing. So I will just go to by Google. And if I go to Taboo Datop, I can just write Tablo Dak Stop download. And you can see the first site, just click on D. Just fill the same information and you get the same download free tell option. Download it after filling the information. You will get a same EXE file and just download it using the EXE file. So if you face any challenges while doing so, you can just feel free to write in the command box. I'll be happy to help you out. Once you will open the taboo deka for the first time, it will look like this. In the above pane, you can see most of the windows, I'm having so many dashboard data open in my system. I've created those many dashboard, but in your screen, you must be seeing the blanks here and you will see some kind of accelerators and sample workbook here. Let us see in the next video, what is the basic interface of tabu, and let us just start our journey of data analysis with taboo. 4. Exploring Interface of Tableau 01: Aaron, let us just go through the interface of taboo. How does it look? So once you first launch, you can see on the left hand side, we will see an option for connecting to any kind of data sources. So you can connect to any flat five pD file, and you also have an option to connect to any SQL server or any cloud based solution. So you can connect to Amazon redshift or SQL server which you'll be doing mostly when you're working in real time domain. And you also have an option to connect to Taboo saver directly. So if you have any published data source that you can connect to, you can do that. On the right hand side, you can see there's some kind of taboo documentation like data is very handy when you're starting new to tabu. And this is a recent workbook, which I've opened that will be shown up here for you to Blank, and there are some accelerator. What does accelerator means you can see this jump start your analysis with rebuilt template. Now what you can do is rebuilt template data have been created by various people or various company. So what you can do is suppose you are working in any finance dashboard you have to create and that accelerator has been created by someone. So you can directly use that accelerator to drive your report. Only thing is you have to change the data sources and you have to change the analysis as per the dataset given to you. So that kind of flexibility is there in tabu. So now what we'll do is we just see how does the tabu interface look when we connect to any kind of connection. So see you in the next one, where will see how to connect to a flat file in tab. 5. Backbone of Tableau: Green and Blue Pill, Dim and Measures: What are dimensions and measures and how we can represent them in Tableau. Basically, whenever you are starting a Genoa tableau, these two terms will be hearing a lot, or you should be knowing about these terms when you are deep diving into Tableau and you are making some records or dashboards. You should know this basic meaning of these two terms because these are the backbone of tableau, you can see. Now let us try to understand what are these two terms. So now whenever we are connecting a dataset to taboo, you can see the Supersto dataset has been loaded here. In the data pane, you can see whenever we are connecting a dataset, the dataset will be divided into two parts. Which are separated by this line, if you can see. The ones which are above the lines are known as dimensions, and the ones which are below this line are known as measures. And on the right hand side, you can see like there's a canvas where your data will. Represented. Okay, so how your data will be presented depends upon what are fields were given rows and column shelves. You can see there are two pills. One is the green pill, and one is the blue pill. Right. So now you can see whenever we suppose we have dragged the subcategory field into the row shelf. You can see it has converted into the blue pill, and the blue pill subcategory is providing SN the heading of the subcategory and the different labels which the subcategory hold the tables, phones, chairs, accessories, the sum of sales is producing as the green pill and the green pill is producing as an axis. You can see the sales number are presented in the form of bar chart, it is producing as an axis. The blue pill you can also take it as a discrete field like the unique field, and the green pill can be considered as the continuous field. Now what we have seen so far is So the green pill produces an excess, right? And this is a continuous field like changing with respect to time. And the blue pill produces as an header or label, and this is the discrete field, like the unique field. Okay. It can be a number also. In this case, it is the sub different subcategory, but number can also be discrete. So this is the basic overview of tableau workspace. I hope you are clear with that. So now let us try to understand one by one. So let us start with the measures field first and try to understand what does measures means. Okay. So let me go to another slide. So you can see, I've listed down the basic properties of measures. So basically, whatever we can aggregate is known as measure. Okay, and it should be a quantitative field like a number field, like a money is there. So that's a quantitative field, the average money spent or the total money spent. You can change the aggregation, like the total as sum or average. You can change the aggregations, sum average or the maximum money spent, or the minimum money spent right. So you can do different kind of aggregation, and it should be a number. So this case, these are known as measures, okay. Now let us move back to our original slide. So you can see profit, quantity, sales discount. These all are numbers, right, and these all can be aggregated, like the maximum discount offered or the minium discount offered to the particular product, or what is the maximum profit made by the superstore or what is the average profit made by superstore? All field can be aggregated, right. So these are known as measures. Okay. So now, let us try to understand what are dimensions. These are the basic properties of dimensions. Dimensions should be qualitative, contain some description or add context to your data. Okay. Dimensions can be descriptive and dimension can also be a discrete field. Suppose, in this case, I've given you example like Mazarism money. From this money, suppose you are buying different things like you are buying apple, you are buying grapes. Apple suppose you are having 100 rupees. Apple cost you suppose 60 rupees and grapes cost you 40 rupees. So this money is distributed in bind two things, right? Apple and grapes. Okay. So this apple and grapes are adding context to your money. Like this money is dividing, right? When these dimensions like the fruits are placed into the picture, right. So this is these are known as dimensions, like the different types of fruits, you can say as dimensions. Okay, so I hope you are clear with that. So now let us try to map these properties in tableau interface. So let me just go back. So now here you can see the categories city, customer name, these all are dimensions right and the product name. So when you select the product name, so product name will be having description suppose you're buying some phone like Apple, suppose you're buying iPhone. So Iphone 13 will have different description right words or you're buying Mantha phone. So it will have different description that the superstool is having, right. So this is also a dimension. Now you can see one more field is there, that is row ID, and it is a number field, right. You can see the hash symbol there. But this is captain dimension. So this is right on yeah, this is right. Why this is right? Because the row ID is the unique ID, or you can say the discrete ID, which contain all the information of all the customer. Okay, so that's why it is known as dimensions. So this comes under the third property which I told you. Like dimension can be a discrete field, and it can also be a number. So this is the basic properties of dimension measures. So I hope you are clear about that. Now let us move on to another slide. Now you might be thinking like these are measures, and we have dimensions. Okay. So if you are dragging dimensions to taboo, so it is a blue pill, discrete field. So you'll be thinking like dimension will always produce as an header or label. And if we drag the measure field, that is represented by the green field like the continuous field, so it will produce as an *** right, but that is not the case. Like dimension can also be represented. As an axis, and measures can also be represented as header or label. It totally depends upon the configuration. We want in our dashboard, like how we want to present our data. That is basically how we want to present our data. That is how dimension measures will work. But only thing is we need to know how to do that. So now let us try to see both examples like one example for measure as a discrete and continuous field, and one example of dimension as discrete and continuous field. So you will get this logic right. Okay, so now let us move on to Tabou and try to load a superhue dataset and try to do one simple activity to represent measure as a continuous and discrete field. Okay, so So now let us go to tableau. So you can see the Superstore to set I have already loaded. So I want to drag the order sheet to the tabu interface, so I can just drag it here. So now let us go to sheet one. Okay, so now I am showing as Mases as discrete. And continuous field. Okay. So I'll be showing both thing. Okay. So now you can see the SAS is a measure. So let me just drag the SAS to the row shelf, and let me just drag the subcategory to the column shelf, and just sort it in descending order and swap rows and axis and just change the view to entire view. And just drag the sales number to the labor shelf. Correct. Now you can see the sum of SAS is a green pill, and it is represented as an axis. So this is a continuous field. Now suppose I want to show some of sales as a discrete field, like a header or a label or as the numbers individual numbers of different subcategory, right? So how we can do that. So what I can do is I can just duplicate this. Okay. And what I can do is I can just rename it and I can just write discrete sales can do duplicate now what we can do is we can change the property from here. We can click on this top down and we can change it to convert to discrete, right? So now if I drag this dimension to the row shelf. So you can see now the numbers are popping up, right. So now, this blue pill is producing as in the header or the label like the discrete sales, and these are different numbers which is popping up right. So now in this particular case, I have represented the measure, that is the sum of sales as an axis that is seen on the right hand side of the canvas and also as the discrete field, right. So this proof the point, we can represent measure as both discrete or the continuous field or we can also say it like that, like we can represent measure as blue pill or as in the green pill. Okay, so I hope you are clear about that. So now, let us just do simple formatting. So in this particular case, we can just do formatting. So just click discrete sales and sales. Control this and we can go to default properties and we can go to number format. And this is a sales number, and this is the currency. So we can do is we can just change it to currency and just two limits and thousands. Okay. So now this is looking nice right. So this is how we can represent Maza as a discrete or continuous field, right? So now let us move on to a second example. So now what we want is we want to as the second point. Now we want to represent the dimension as the discrete and continuous field. Right. Now suppose I want to see like I want to see the yearly or monthly sales, suppose. So what I will do is I will just dug the sales to the row shelf and just dire view, and it is a year sum of sales by different years, right? So now what I want is if I show the filter in the ear field. You can see this dimension like this blue pill is producing us in the header, like the ear header and the labels, and we can only select A one. We cannot see a continuous field. We have to select from these discrete numbers. We can select one number or we can select all the numbers, right. So now what I want is I want to convert this filter into the continuous filter in this particular case. I'm not converting this pill. I'm converting the filter. I'm connecting the blue pill filter. So filter also we can do that. Okay. Now suppose I want to change it to continuous. What I do is I can just click on this top down and just convert it into the continuous field. Once I convert into continuous field, and I again show the filter, and I just remove this card, just remove this blue pill, and just Control click this new Breen pill and cannot filter. So you can see a bunch of option will available to you. So now if I click on range of dates, so this will show me the starting date and the end date and I click on Apply and once I click on show filter, now you can see now it showing the continuous filter, you can check in all the dates that are present in this particular dataset and you can change it right. So this shows you can represent dimension as a discrete as well as continuous filter. I hope that clear the points and you are able to understand the concept. 6. Exploring Interface of Tableau 02: Welcome back. So in this particular video, we'll just see how to connect to that file and we'll just explore the taboo interface. Like how does it look and how you can get different kind of visualizations in taboo. So I hope you're excited by now. So the first thing is, you can see an option for connecting to any File option here. So you can just click on the Microsoft Excel file. Then you can just go to your document folder. So in the document folder, you can see an option for my taboo repository, and you can see option for data sources. Then just go to the IsentFolder that you have and just go to US and just like the superstore data set. Certainly available to you. So once you connect to Superstore dataset, so what will happen is you will see interface like this. So this is a data source pane. So in the data source pan, what happens is, you can see all the sheets data available inside this Excel. So the look will be different if I load a database here. So mostly when you're working on real time, so you'll be working on database. So our case study will be based on the flat files, but no need to worry about this. I will also show you the option like how you can connect to database. The process is similar. Only thing is the connection is different. Okay. So now the thing is, you can see an option for orders, people and return table, three tables are available inside the Superstore. Orders contain the order of the people who are buying from Superstore. Return table contains a return order that the person has returned the order, and the table contains manager name. Okay. So what we want to do is we want to see the orders table as of now. So I have to do is I will just drag it to the right hand side. So you can see, this is my order table. And now the data table has been rooted in the down. You can see we have different column row ID, order ID, order date, ship date, shipment, more customer ID, all the related data have been added tableau. Okay. And one more way to see the data is, you can see on the right hand side, this icon view data. So if you click on this, it will show in a smaller pane, but it can show you the data data show you the data, how does it look? What are the columns available and what is the value for the first 10,000 rows? Okay. So now the thing is, like, once you load the data in Tableau, so you can see there's an option for connection. So there are two types of connection in taboo. One is like live connection and second is the extra connection. Okay. So what does the difference between live and extra connections? So that is very important, e comes to taboo when you're starting your journey. So the thing is like, you can just remember like this. So live connection means like you are connecting, you can see the wording also here. You can connect directly to your data. So basically, speed of your data source will determine performance. So what will happen is like if you have 1 million of million say suppose for example, you have a database and you want table that has 1 million of record, and every day the record is adding up on the day level. Okay. And you have connected as a live connection to DAT. So what will happen is so every time you will load your report, you have radio report. So every time the data is refresh, so it will fetch live, right. So it can hamper the performance because it is fetching live and it is adding additional record to your million of record, right. So at that time, what we prefer is like we use the Eta connection. So what does Eta connection do is so when you have do report, so Eta connection will take a snapshot of your data that you valid, uh, uh, connected with. Okay. Then what happens is like you just scheduled afresh option in taboo server, like you want to refresh your dashboard, like if it's weekly or bi weekly or daily level. So what will happen is like at certain point of the day, like it will refresh the data source, so it will not hamper the performance, because it is refreshing only at a particular time of our day, right, or a particular time in a week or two times in a week. So data way extra connections are very good to go, like when we work in creating a dashboard. So this is one of the quotien that can come to you in mind when you're starting on Genuine taboo. So I hope you're clear with that. And we use dive connection in very rare condition. Like, suppose if you have a weather forecast data, and you have to see the daily amount of data, how the weather forecast is there. And data is limited, like it is lesser in volume. So at daytime, you can use dive connection, but it can still can hamper the performance, like if the data, grows gradually year by year. Okay. So the next thing is, you can see option for the filter icon on the right hand side. So this is known as the data source filter, so we'll be covering in the later part of the session. So now let's just move on to the down one. So you can see it down you can see the right hand side is the data pane and the left hand side is known as the metadata. So metadata means it is telling you about the data, what are the columns available in that? What is the data type available to that? So you can see this number, hashtag, ABC, calendar icon, geographical icon, and this uh different thing, right? So what does represent. I represent hashtag means it is automatic field. ABC means it is a categorical field. Then then you have globe icon. That means it is geographical field, represent the half is dian. Okay. So that kind of influence we can take from this ato type. Okay. So now let us just move on to sheet one. So if I go to sheet one, show me where I want to save the abstract, the snapshot of my data. So I'll just save it because it is a flat file, so it will save locally in my system. Okay. So now the thing is, this is the interface, when you load taboo for the first time. So in the left hand side, you can see data pane. So one data source is connected here. That is extra connection, the loose lend icon, and the arrow symbol, it has an extra connection. If it is a live connection we a simple lenticon. Okay. So now coming forward to this thing, so you can see there are two things, so you can see measure names and measure values. Okay. And you have one thin line, if you can see that. So if I drag anything from this thing, so you can see two terminology, dimensions and measures. Okay. So what does dimensional measure mean in tableau? Okay. So basically, like, let us just see in the next video, what does dimensional measure means. And then what we'll do is, like, we'll just deep dive into the taboo interface and we'll just be some kind of visualization in tabu. And we'll also see like when we should use which kind of visualization when we're creating some kind of report and some kind of analysis. So see 7. Types of Viz : When to use based on Real time data analysis?: So now let's just see how to bid a different kind of jation. So suppose, let me just create a line chart for you. So when we use line chat chat, we should understand. So the thing is, whenever you see a time series data, if you're analyzing anything about time or you're comparing two different competitors, if you have Apple and Samsung and you're comparing here over here, what is the growth rate of Samsung and Apple? So that time, you can represent in a line format. So it is a very good way to for the audience to analyze the data. So let me just do it for you. So suppose I have a ord, and if I drag it to the column shelf, so you can see the thing. So if I drag to column shelf, so the thing is it will go horizontally. If I go into rowsel it'll go vertically okay. So this is the alignment it follows. Like if I drag anything to rose, it will in vertical fashion, you can see the icon in the left hand side, the three dots. So three dots represent how your data will be interpreted when you drag it into rows or column. So if I drag it to column, it will be in the horizontal pattern. Right. So now thing is what I want to do is I want to see the SAS number, like how the SAS going year by year. Okay. So what I can do is I can just drag this SAS to the row shelf. Okay, I can just change it to entire view. So now you can see this is the trend. So what I can do is I can just click on this drop down and I can just change it to month view, for all the months. So now you can see it is very easy way, right? I am just seeing like month on month, like how my superstore is performing. Like, now the thing is, if you have different comparators I told you, suppose I'm seeing for the different regions in this dataset. So I have like four region here. So if I want to see the four region which is performing good. So what I can do is I can just drag this to the color shelf. So what does this color shelf means is, so the line will be divided on the basis of the region. So if I click on Color shelf, so you can see now the three regions have been divided for central region for each region for South region and for West region. I can see the individual sales number, right? So this is how I can interpret the thing, right? So one other thing is nowadays is looking a little bit clustered. So what I can do is I can just change it to table calculation. So what does table calculation means, don't need to worry about it. Just see as of now, we'll be covering later part of video, what is table calculation? How does it work? So what I will do is I just click on this drop down and you can see an option for quick table calculation, and you see an option for running total. So what does running total means it will just cumulative. It will just add up for all the months I will give you the cumulative number how it is going on. So if I click on it, now it is much more clean. You can see the cumulative SAS of South region is. So if I drag this sum of SAS if I want to show as a data labels in the right hand side, what I can do is I can just drag it to Labor Shelf. Adithm show me for all the labels. So what I can do is I can just customize it. So if you see option for labor shelf here, if I click on the label, you can see a bunch of ready option, you can just adds a text what you want to give, you can just change the font size. You can just match mark, color, the font color. Align top align vertical align, or if you want to give a wrap text on or off, you can do that. You want to show minium maximum, the line ends. So as if now, I want to show the labors at a line ends. Okay. And all you want and other lines. Okay, so I can't do that. So now you can see for central region, the total cumulative sales is like three line 91,000. For central region is 53000, for west region is the most sem 39,000, so you can see a quick inference, like the sales for this west region and east region are increasing at a rapid amount as compared to central and South region. Right. So this is how the line graph is, like, quickly, we can compare the two particular competitors, right, like into competed regions we can complete. We can just analyze easily, right? So that is where we should use that kind of gon. And you've also understood here, like, how you can use the colors thing and how to use the label thing, how you can format a label. Okay. Now the next thing is, I can also change the color palette of the labels if I want to do. So what you can do is just click on this drop down, addit colors and an option for selecting the bunch of colors. If you click on this drop down, you can see an entire list to Slack form. So what I will do is I will just slack form some other thing. So for example, I will just use the Facebook one. And what I can do is either I can click on assigned color palette, so it will assign for me. Or what I can do is I'll just do for this assigned color palette. It will do for me. Or what I can do is I can just manually just double click on it, and you can just let the X code here if you have any X code, or you can also pick the color from screen and you can just drag it this color I want. You can use this kind of thing as well. Okay, so click on APi, click on Okay. Perfect. So for Central all just do it a little bit darker color. Okay. So as of now, I can just using random colors. Okay. So this is how you can change the colors in tableau. Okay. So now the next thing is, like, let us just move on to another kind of visualization. Suppose I want to get a bar chart. So what kind of situation I should do. Okay? Like, suppose if I having any subcategory or any kind of dimension, and you have more than five subcategories to it. So for example, in my dimension, I have subcategory. So if I drag it to row Shelf, so you can see I have around 17 row items. Okay. So if I want to see the sales number for all the subcategory. Okay. So what I can do, I can use the Brogon It'll easy for me, right? So if I click the sales number, and if you can see the arrow for arranging in designing order, just click on that, and the standard view you can just click to entire view. Okay, now you can see it is easy way, we can represent how those are going for each of those subcategory. Okay. So suppose if the subcategory are less, subcor only three subcategories, then there's a dilemma, either you should use bar chart or pie chart. So the thing is, like, it depends upon the user perspective. Like, if they want to show a bar or pie chart, both are correct. But the thing is, like, if the subcategories, if any dimension is having more than five subcategories. Okay, then I should you should always use the bar chart because it is very handy because if you use a doughnut chart or a pie chart, what will happen is like you cannot see each window will be divided, so it will look clustered. I'll just show in a bit. So as if now, we have created a barchat for this. So now what we'll do is uh, for example, let me just show you now only. So if I click on showing button, if I change it to do not chart. So you can see a show button is available. So you can create some kind of pre built visualization, once you have selectrial dimension measure. So if I click on this, so it will create a pie chart for me. So you can see now it is so much clusters more than five to seven subcategories. So it is very, um, the information is getting lost. So if I'm clicking the bar chart, control that. I can see I can easily see the chair is the winner and the phones the winner. Like in terms of sales, right? So I can just dig the sales to labels. I want to show the labels here. And the thing is, suppose I want to show, what are the profitable and non profitable categories in my and you decide, Okay. So what I can do is I can just drag the profit to the color shelf. So what does color shelf will do is it just divide the color based on the profit. It's a factly con. So you can see now the colors divided. So orange represent like it is going on losses, but the sales number are high, and like dark color means, it is going profit. It is profit is also there and the sales number is also high. Okay. So now you can see for this table subcategory, the sales are more. Like SAS are making top four sales top four sees it is making 8,000, but it is on losses. So you have to investigate, there in losses. There might be a case like the superstars given too much discount in the TBAs that people are buying from that, but the manufacturing cost is more of the TBs. So that kind of scenario can be there, so you have to investigate that. So now what I can do is I can just change the color coding for this as well. So click on Add Colors and I can just do it a red green diverging and click on Brian. Click on Okay. Perfect. So now I can see this change light. So now the thing is, let us just move on to another kind of Ashm. So let me just create a Dan chart. Okay. So now the thing is, if I create two Dan chart. So what I have to do is I can either create from the showing button or I can just create from this manually. So for example, like, if I want to see for the of what you can say is let me just check what are the things that segment. So if I create to Rocha, you have three segment, consumer segment, corporate segment, and homo segment. If I want to see which segment is contributing most for most percentage of the sales. Okay. So a daytime you have the two choices. Either you can create a barbation or either you can create a door chart. But as you know it is only three categories, you can say. So I can use a door chart. It will be much more effective. Okay. So now let's just see how we can create. So the first thing is you have to change this marshal to Pi and you have to drag the measure into your angle. Okay, so it'll form a circle here 60 degree. So now what you want to do is how you want this circle to be cut it. So you want the circle to be cut it on the base of the segment, right. So you can just drag the segment to the color shell. Perfect. And now what you can do is you can just Control click sum of says to label and Control click segment to the labels. Okay. And now what you can do is you can just use table calculation, drop down, quick table calculation, percentage of total. So no need to worry, we'll be covering this table calculation later part. Okay. So now the thing is I can just change the color code. So as of now, I don't like this color code, I can just change this MO Monday, assign this color palette. Okay. Okay, perfect. So you can see, or I can just change another color code. I'm also not liking this. So as of now, Philippines not that much attractive. Okay. This is, like, too much highlighting. So don't need to focus on the color thing, as of now, because as I'm going the random color thing. But when you're creating a report, it should be extra cautious, like, using the color code because it should be like on the basis of the dashboard design, dative creating. So it should be consistent. Okay. Okay, so I'm just using this color palette. Okay. So just to represent you so you can see visibly. Okay. So now you can see that consumer section is the highest series maker, 50 percentage of sales coming from the consumer section, and 30% is coming from corporate and the lowest is the home office right. So you can easily identify this. Like if I convert into bar wave, so you can see this is also one of the way. I can just remove the sum of sales. This is also one of the way I can just drag to sales. This is also one of the way. But Rona Chile is looking like much more interesting, right, and it is much more intuitive. So I can just go back to Control. Okay. So now the thing is like, this is the pie chart that you can already make using the Showi button or the process that I have shown you. So now the thing is like, suppose I want to convert this word donut chart, that is like trending and look much more cleaner. Okay. So how to do so. Okay, so there's a trick involved in taboo like to create a doughnut chart. So the trick is very simple. So the first thing is like whenever I want to create a axis. So now since you have learned about dimensions a green and blue peel, so if you want to create an axis, what you do is you just create one calculon. You just create one measure. So if I create minium one, so what it will do is it will just create an aggregated field and it will be a green pale, right. And the green pale will give me the axis. So I can just create Canter, so you can see an axis has been created. Now what I can do is I can just duplicate it, Control click and duplicate. So you can see two donut charts there, right? So now what I can do is in the second one. You can see two pie. Second pill, I can just remove all the things. Okay. And now what I can do is the first pale, I can just increase the size. And second pale, what I can do, I can just put this circle above this. So that means like I'm just doing a dual axis thing. So just click on this drop down an option for du Lxs. Click on that. So you can see dual axis thing. So now I can change the color to white. Okay. And now I can just make some adjustment. I can just increase size little bit. Perfect. So I can see a donut chart is ready. All the thing is, I could the formatting. So how to do formatting, right click on this. I don't want to show the header, show the header, right click on this format. And you can see an option for format bunch option available here. So this is for text. This is for alignment. This is for color. This is for borders, and this is for grid lines. So for gridlines, I want to do as a nun. So as you know, you can see a column grid line, so I can just go to columns and do a gridlines nun. So now you can see my is much more cleaner. I can just say this file. So this is how we created O hart, and we should use Do not chart near. So is vis type. So you should use Don chart or Pi chart, like when you have less than one or less than five categories, I would suggest that I like it is more than four or five, you can use Par chart at that kind of situation. Okay. So I hope you are learning it. So now the thing is, we also you can see how, you can see this thing. So this is known as a tool tape in W. So Cool tape means I can show the value. So you can also customize it. So if I click on this tool tape, icon. So I can customize it, so I can just remove this. I only want segment, so I can see the segment. Then I want just percentage of sales. Okay. And I just don't want this. And you can also insert some kind of sheets and different measure if you want to. So as of now, I'll just leave as it is, and I can just write percentage contribution. Okay, and click on Okay. So now click so you can see consumer person contribution 50 percentage, 18%, 30%. So it is not going into rebate. So you can do more with this setup. So only thing is I just wanted to show you the different features that is available. And you suppose that you want to add anything that title. So if you click on the title, double click on it, so you can see the option for Insert option. Okay. So if you want to add anything, so what you can do is you can just add it from here, like segment if I want to add. So I can just add it so I can say all segment is selected. So I just wanted to show you, it doesn't make sense, like what I'm doing here. So now I hope you're okay with it. So now what we'll do is we'll just go to another sheet and just create a map visualization. So suppose you have any geographical field. So in this case, I have stayed. So what I can do is I can just double click on it, so it will create a map for. You can see it is showing me 59 unknown, just click on it, click on Added location. So you can see now it is choosing my country to be India because I am belonging to India. But the data set which we are connected is from US. Okay. So what we have to do is just click on this drop down and take it from field. So from from the data source to pick the state. So if I take from field, so then it'll take the correct state. So if I click on, okay. So now I can see the dotted line is there right. So some kind of map we are getting. So now the thing is I can just change the mark Self to map one. So now you can see a map has been there. Only thing is I can just drag the state from left hand side. To the labors, surface to the labors. Okay. And now I can give the color code. Like suppose I want to see, like, based on profit, so I can just drag the profit to Color Shelf. So you can see now the profit has been changing, so you can see taxes is going on losses, and California is the profitable country. And this also is profitable country and Washington as well. And Colorado, Ohio is also going on losses. So I can just change the color palette, Addit colors and KlicnO the colour part I want to choose. So I'm choosing red black, diverging. Perfect. So now it's looking much more better right. So now the thing is I can also remove the additional background, so you can see I don't want to show this additional background Northwest territory Maxio. So what I can do is t click on it. You have an option for map option for removing this Zoom icon and plus icon, so I click on this. So you see an option for removing all this. So if you want to do that, you can do that. And then the option is background layer. So if you click on that, you have an option for washout. So just do it 200%. So you can see now it is much more cleaner right. So this is how you can do it. So now the thing is, I will show you one more thing. So suppose, I want to show a tool tip, okay, advanced tool tip. So what I can do is I want to show this language dion on my App diction, on the base of State. I'm hovering over. Okay. So what I can do is I can just go to Tool tape and I can see an option for insert sheet and just insert a line chart. Okay. Then you can give the minimum maxim width. I'm giving us a 500 as of now, and click on okay. So I hover over. So you can see for uh, taxes. This is the thing central sion for California. And for this, you can see all the gelation and cette. So we can do it like when it is necessary, so just change it. So suppose I want to add a bar graph here, or chart here. Okay, click on Okay. So you can see the shing for taxes this is the percentage distribution. For California, this is the percentage distribution. So you can see how coal is detert. So the thing is we have to use this when it is necessary and when our situation demands. So you should know this set is available in taboo. Okay. So I hope you're getting the point and getting your hands on taboo. So these are the four basic chart that we mostly use. And so, like, we'll be covering, like, the other charts that we making like table visuation or, like, kind of heat map. So we just cover in the later part of the session when we'll do the case study. So we'll see how to, like, create different kind of viuation in Tableau. So see you in the next video. 8. Introducing the Case Study: So now is the perfect time for me to introduce the case study that we'll be working upon. So we'll be dealing with the healthcare analytics. So we'll be dealing with the healthcare domain data this time. And the business problem that we have is suppose you've been hired as an analytic consultant for California General Hospital. And your main aim is to understand about the hospital recent performance, like how the hospital performance is been through the entire years, right? So what you have to do is, you have to build a KPL dashboard for the executive team. The CEO and you have to summarize all your insight that you can get from the data and present present to the stakeholder, so they can take action based on that, that is the main aim that we have to do in this current project. Some of the key questions which I've listed below is you can analyze these many things. So you can analyze how many patients are being getting admitted or readmitted over time. How much is the duration, the patients are staying in a hospital? What is the average cost per visit? How many procedures have been covered by insurance? Basically what the tell us we also have the insurance related data with us. As of now, I know, we have not seen a data. So in the next video, we'll be seeing deep diving into the data dictionary and we'll understand what are the data we have available in our hand. And then we'll understand the concept of fact and dimension table and then we'll move forward to data modeling and then we'll move to visualizations. So there's a lot to unpack in this course. So I hope you guys are excited and you are ready to deep dive into the case study. So solidify your taboo knowledge plus the business knowledge that is lagging today's world. So we'll be covering both in this course. So see you in the next video. We'll see what are the data available to us and we'll understand the data dictionary first. So yeah, bye. 9. Understanding Data Dictionary: So before deep diving into taboo, let us understand about the data dictionary that we have in hand. So what does data dictionary means? Like if you're new to Analytics domain, so this might be new for you, right? So let me just explain to you what does data ditonary means first, then we'll deep dive into how we can read that or how we can interpret that. Okay. So basically, data dictionary is like nothing. Like data dictionary basically contains all the data that has been available to you, all the tables, all the views in which your data is stored. So that list is there in that list, you have the column name, what is the column available in this particular table. And what does that column means? So you have to be solidifying your knowledge first right. You have to understand about what your data is about. Like if you don't know about your data, then you cannot analyze your data, right? So that is the first step. So the thing is like the data dictionary, in most of the instance is not available to you, like if you are working on a real time project. So in that case, what you can do is like the tables that you have been working upon or the views like that you have created in your project life cycle, you can create a data dictionary for your reference. So that can be easy for your juniors, or it can be also helpful for the other teammates that you have been working upon. So that is what is about data dictionary. So let us just understand one by one. What are the table available with us? You can see I have three columns, table, field, and description. Table contains what is the tables been available to us and what are the field. Field means what are the column available to us and the description, what is the description of that particular column. Okay. So in this particular case study, we have five tables. We have encounters table, organization table, patient table, peers table, and the procedure table. So I have highlighted them with a different color so you can easily identify which table it contains. So we'll go one by one and we'll understand what all the different tables is about. Okay. The first table is like the encounter table, it contains the patient encounter data. So ID encounter ID, it contains the start and stop time of the encounter. Basically, encounter means if the patient has been admitted to hospital and if they are doing some kind of surgery or some kind of procedure to them, some kind of treatment to them so that you can deal as a encounter. Then we contain the patient that is foreign key. Basically, it contains the unique patient ID, what is the patient ID, organization ID, and the payer ID. Then we have encounter class. So encounter class, you can see we have description. So encounter class means, whether the patient is in emergency situation in patient like it is like incoming patient or required ambulance ambulatory or just wellness room he can share or urgent care is needed. So this is the encounter class that we have. Code, just a code based description of the encounter. What is the description thing? And what is the cost associated with it? Like the base cost, total claim cost and the pay cost that is available to us. And the reason has been admitted to. So what is the disease he's facing, right? So that does what contain the encounter table. So now let us move on to the organization table. So organization table is nothing just the hospital details it contain like hospital name, hospital address, city it belongs to state it belongs to ZIP code and their latitude, longitude detail. Okay. Same contains with the patient one. The patient contain the patient level detail like what country is being and what is the race, ethnicity, gender, all that kind of stuff is given in the patient table. Now comes the payers table. So payers table is like a insurance pay table. So the different in US, what happens is there's a insurance companies there. So you have to buy an insurance program with the insurance company. Certain amount will be being paid by the insurance partner, and some amount you have to pay. Like, there's a thing is 50% will be paid by insurance partner. So there are schemes that like different appear like give to the clients. So that is what it is. And then comes the procedure table. So it contains, like when the procedure started, like the operation started and the stop, and what is the count ID and what's the description base cost and the reason of the disease he's been facing upon. So I hope you're clear with it. So now let us just move on to the one further step. So what we are going to do is like we are going to identify the key. So the first thing is, you have to identify the key in it, what is the primary and foreign key. And then you have to identify which table it belongs to, whether it is a fact table or whether it is a dimension table. So in the next video, we'll see how to identify keys in the tables, like how to identify primary and foreign key, and then we'll dig them into the tables, like how we can identify it is a dimension table or a fact table. Okay, so I hope you guys are excited. So let us just see in the next video. 10. Fact & Dimension Table, Types of Keys: So welcome back. So in this video, we'll understand what are the different kind of keys. So the main two keys, we'll be understanding. So let me just move to my notion first. So if you're new to databases, if this is the first time you are dealing with the databases, so you might be not aware of the primary and the foreign key. So let me just give a quick background, like what does primary and a foreign key means. So basically, primary key are the keys, like we uniquely identified a particular row in a particular table. So you can see in this user table, we have user ID, username and email. Like each user name will be given the unique identifier like one, two. So this is the primary key for the user table. Suppose you have another table that contain the order ID, if the order has been placed and which user have bought it, that is a user ID and the product that they have bought. Okay. So in this case, you can see the order ID is the unique identified for the order table. The user ID is the foreign key. So basically, user ID is the primary key to another table. So basically foreign key, basically, it is the primary key, primary key to another table and tell about the relationship between the two tables, they can link to. So that is the main difference, you can say about the primary and foreign key. Now let us just move on to Excel thing and let us just identify what are the primary and foreign key. So you can see we'll go with the second one first. So you can see with the organization one. So you have only one ID field that uniquely identified, which organization it belongs to. So this is the primary key for the organization table. So I'm just citing as PK, so primary key. Okay. And for the patient one, you have the patient ID. So patient ID will be the primary key which uniquely identified the patient name, right? We can also take patient name as the uniq identified. But as if now you can see first, middle, and last name is there, and it can happen like the person the person can have same name, right, so it will not be the unique identifier. Zip code can be one of the unique identifier, but you have to check in the data. What is the unique identifier. But in the data dictonary it has already been provided. Like the ID is the primary key, so we can just list it down as a primary key. Okay. But in some instances, it can be also there Zip code can be primary key for some instance a phone number can be primary because each person can have one phone number, right. So that kind of thing can be there. So now comes the pair one. So pair one, you can see the insurance pair. So the ID field is there, so that is the primary key. Okay. And in the procedure table, we have patient and encounter ID, so we don't have any primary key here. Okay. So now let us just move on to the encounter table. So in the encounter table, you can see the encounter ID. So if the person has, has registered the hospital, so this will be the primary key, right? And then comes the patient organization pair, right? So patient you can see it is the patient ID, basically. So patient ID. So it is the foreign key because like patient ID is the unique identifier in the patient table, right? And it is like linking the relationship between these two table. So this will be the foreign key. That is Byzantine encounter table, that is related to the patient table. That is the primary key in the patient table, right? So this we can write as a foreign key. Same with the organization. Organization will be the foreign key in this encounter table, but primary key to the organization table, right. And then comes the payer table. So payer table also foreign key. Right. Now we'll come to organization table. So in organization table, there is no other key field, so there's only one primary key. And in patient also, we only have one primary key, and pairs also we have one primary key. Okay. Now moving on to the procedure one. So in the procedure, we can see patient and encounter ID we have. So we have two foreign keys here. So we can write this as foreign key 1 second. F k and foreign key, I can just set it again, foreign key. And there's no procedure ID or something like that that can be unique identifier for this table. So there's only foreign key available in the procedure table. Okay. So now the thing is, we should look for the measures. Like what are the business measures that we are dealing with what the KPI is like that we have or what are the measures. Measures means like basic thing that we are measuring, right, but can be aggregated, you can say. Okay. So you can see in the first table, encounter table, we have three things like the encounter cost, total claim cost and the peer coverage. So that is the business might be looking forward to it, right? So this is the measure that have been available in this first table. So I can just write this as measure measure measure. Okay. In the organization table, if you see, I have ID that is the primary key, the name, address, city, state, all other dimensions are there. So there's nothing measure field here. So no need to worry, if you're not available or not aware about the dimension measure. So let me just give you a quick overview about it. So basically, dimensions are the one which tell about descriptive properties. Like you can see in the organization table name tell about the name of the organization. This is a descriptive thing. Address is a descriptive thing, right? So this ID is the numeric field, but it is uniquely identifying like the organization, right? So this is also the dimension. And measure means the things which we can aggregate it. So the thing is, you can see the total claim cost. So we can identify, what is the average claim cost? What is the maximum claim cost paid by the peers. So this we can aggregate, right? So these are measures, and these are dimensions and measures difference. Okay. So we'll see all this live in action in table, so no need to worry. So just to help you understand the basic concept of primary key and the foreign key, this video is meant for you. You can see for the patient one, we have only patient related data, so, same basically no measure field here. And the pair also, we don't have any measure field. In the procedure table, you can see, I have base cost. That is like we are telling you the cost that had been taken for the particular procedure, particular surgery, we can say. So this is also a measure, we can just write this as a measure. Okay. So now I hope you have understand the difference between primary and the foreign key. So let me just give you a quick recap. Primary key, other keys like unqually identified the particular column in the table. The foreign keys are the ones which can be primary key to the different tables, but it can form the relationship between two tablet is linked to another table. So that way you can understand primary key and the foreign key, and we've also seen how to identify dimension and measure in the data dictionary. With the help of dt, we can identify which table it belongs to. Okay. The thing is the dimensions table are the ones, which contains the descriptive properties. And the fact tables are the one which contain the particular measures, and measure business measure that we are looking forward, and will contain all the foreign key in it. Okay. So you can see in the first table encounter table, we have the measures, we have the primary key, but we also have all the foreign keys, like most of the foreign keys, three tables are linked with the encounter table, right? So basically, this will be the fact table to us because it contains the measure and it also contains the foreign keys in the table. So this is the quick identifier you can take, like when you are dealing to identify what the fact table and dimension table, and this question can also be asked in an interview, like if you are deep diving into interviews. So this is the most common question that the interview can ask you. So the thing is, what I will do is I will just do mergin Center and I will just write this as fact table or fact will write. Okay. Now comes the organization table, so it doesn't contain any foreign key, and it doesn't contain any measure. It contains only organization related data. So this will be the dimension table. Okay. And same goes with the patient because it contains the patient related data. So this will be also dimension table, and then comes the payer related data. So this also will be the dimension table, right. So now I will just give you 20 seconds, guess which it will belongs to. So I hope you were able to guesses properly because you can see, there are two foreign keys that I linked, and we also have a measure. So this will be also the fact table for us. So this will also act as a fact table. So I'll just two quick merge center and I'll just write as fact. So what I can do is I can just identify the fact table with orange color. For a reference. Okay. And for the dimension table, I can just give it as a blue or I can just give different color of blue because I've already used that blue. So I can just give that as a light blue. I guess this is perfect. Okay. And what I can do is I can just 1 second, just give me 1 second. I will just add this and just move it to top. Okay. Perfect. So now you have understand, right, why our data dictionary are more important. So if we get the data dictionary in our hand, we can easily identify the primary and the foreign keys, how the tables are being linked, and what are the fact table and dimension table. So I hope you guys were able to understand this concept. And if you guys face some other problem, like if you choose the first time, you can also rewatch the video, and you can also feel free to write in the comment box what are the challenges you faced or what are the quotients you have. I'll be happy to interact with you. So in the next video, we'll deep dive into the data modeling. We'll see how to link our fact and dimension table and how we can create data modeling and how we can interrelated table together in Tableau. So that would be good for our dashboard creation and the report creation. So see you in the next video. 11. Star and Snowflake Schema: So now since we have studied about what are the fact table and dimension table, so now let us just understand about the schema first and then we'll deep dive into Tableau to build a data model, live in action. So I hope you guys are excited. So before deep diving into tabu, let me just move on to my notion. So these are the two schemas that mostly the data modeling happens. So one is the sta flex schema and second is the Snowflax schema. So what does staff schema means? So basically, what does star schema means is Like suppose you have fact table, which is in between. So you can see in this example, like the sales data is the fact table, which is in between, and all the dimensions table are linked to the fact table together. That will like it form a shape of star, so that's why it is known as the star schema. So basically, it is nothing like if it is not forming the shape of star also, you cannot imagine, right star it is for the interpretation, like the people have invented star schema, they have represented that way and they have named as star schema. So the thing is if suppose you have a fact table, and you have to link the dimension table all together. Okay, with a one fact table. So that is star schema. And Snowflx schema is suppose you have one fact table that is connected to one dimension table, and that dimension table is connected to another dimension table. Then dimension table is throw another dimension table. Basically, if you have a sub series of dimension table, that is connected to the fact table. So that is known as a Snowfla schema. This is the easiest way you can remember, if there's a one fact table and it's linked to all the dimension table, that is tar schema as Snowflx Schema like if all the dimension tables are linked with one fact table, design, Snowflx Schema. Mostly, we use star schema because it is performance performance it increases because Snowflx schema, like it can hamper the performance because it contains dimension table that contains descriptive properties, and it is like you have to filter three dimension table to get the result. So there are performance challenges. But in most of the cases in the data modeling, we use both star soface schema, but if possible, we should try staar schema. Okay. So now the thing is, I hope you are able to understand the basic structure of it. So now let us just move on to tabau and see how to implement data modeling. 12. Multi-fact Relationship in Tableau-Case Study: So now is the correct time to deep dive into tabu and build our first data model. So this will be a quick hands on exercise for you. And this is how mostly like if you're working on any industry domain or any copit you are working upon. So this is the step like you have to take which I will be showing you now. So mostly the thing is only instead of flat five, we'll be using one SQL SOA connection, and SQL like we'll be having these kind of tables or in right shape or Snowflake. Any Cloud solution based solution will be there, and we have to build a data model. Okay. So now since we have Beta data dictionary, and we have also highlighted the key and the table, table linked to dimension of fact table. So now you will understand why data dictiary are so much important and why it will help us to ease our greater data model. Okay. The first thing is what I will do is I will just connect to my text file and we'll just click on Encounters or any other file. Okay. Then you can see all the file have been loaded on the left hand side, you can see all the files which are present in this folder, and I'll be doing extra connection because you know by now, why do we need extract connection. So do let me know in the command box. I'll be happy to interact with you. So now in the down, you can see right hand side is the data view and the left hand side is the metadata. So metadata just tell us about what are the fields available to us and what are the datatypes available to us? And we can also change the data type from here. Okay. Then you can see there are numerical data time, string and two more datatypes are there spatial and Boolean. So Boolean means whenever you have condition like two or false, then Tableau identified data a boolean variable. Okay. And spatial means like suppose you have any geographical field where you want to use geolocations or some kind of hexagonal mapping, then you will use the special coordinates. So daytime we use spatial. Then comes the two options which are available, geographical role and image rule. So I'll just give a quick level overview as of now, but we'll be also depving into later section of the video. I will just tell you when to use them and to not use. So geographical dole basically, suppose you have a zip code, and zip code is given as a string field. So you have to highlight in the map visualization. So what you have to do is you have to give the zip as a geographical location as zip code what Tableu will do is Table will identify the latitude and longitude by itself using the zip code number and then it plot in the map visualization. So that time geographical dole comes handy. Second one is the image role. So basically, if you have any column which contains all the URL. So what you have to do is just you have to give that column image as URL. So what Tableu will do is like Tableu will deal that column as a URL and fetch the image for you live directly from that website or any other source, and you don't have to import any image like a what you can say is, you cannot import your image one by one. Like manually, you don't have to do the task. So this seat is very cool. So now what we'll do is we'll focus upon the data modeling section. So I will just scroll this down. So now you can see in the top, there are options for data modeling. So the thing is, we can do either joins operation or relationship operation. Okay. So in this data modeling section, the Katudy we're solving, we'll be going to the relationship one. So we'll see why do we use relationship or joins in a later part of the video. Okay. So let me just do that. So how to do a relationship is, if I drag any other column. So if I drag this, you can see a noodle icon. Okay. So whenever you see a noodle icon, so that means it is a relationship, and it happens on the logical layer of the tableau, which is like initial layer. And if you want to do join, I will just drag this out. So you have to double click on this, and this is the physical layer. So if I drag anything now, so now you will see the thing will be different before you sing the noodle sign. And now we are seeing a win diagram. So in diagram just represent which kind of join I want to do. Okay, so no need to worry, we'll deep dive into a later on, so I'll just remove this. So now what we'll do is we just focus upon building a data model according to the case study that you're solving, you can see we have two fact table encounter table and the procedure table. So before, in 2023 was below that. L Tableau doesn't offer multiple fact relationship. So this is the new feature that tableau offered. Now we can connect to multiple fact relationship. That's why I have chosen this case study for the course so that it will be ahead of many people who no tab might don't know about this feature and might not have practice in real life. So it'll be hands on and you are one way ahead of them. I just wanted to appreciate you guys, those who went all in this course. So just to tell you you are one step ahead. So we'll see. So now what we have to do is first we'll dive the fact table. So I have encounter table, so I'll just interact the encounter table first. Okay. So now you can see it is asking option for add a base table. Base table means another table. So another fact table is like we have a procure table, so I'll just add as a new base table. Okay. Now what we'll do is we'll just go one by one. So we'll just see how our fact table are connected. So now, since we have maintain our data dictionary, so it will be easy for us. So you can see in counter table is connected two, three foreign keys. Patient organization, and pair. Okay. So what we have to do is we have to just connect to patient. Organization and pair. Okay. But before deep diving into simultaneously, we have to just see how we want to join them, how I want to relate them. You can see as if now Tableau has identified encounter ID with patient ID. That is wrong, right? We have to connect the patient ID with the patient ID, right? So we have to change this to patient. So this patient will be called to patient ID. Now it's correct and same with the organization one. So again, Tableau has identified gs. We have to connect with organization ID with organization ID, and the last table is pair one. So again, we have to pay RID with pair ID. Okay. Perfect. So now moving on to the next fact table. So this fact table is connected to two foreign keys. So that means we have to connect with patient and encounter table. So what we have to do is just click on the plus icon and drag it to patient ID. That's simple. Only thing is you have to just give the correct column to Link otherwise, your analysis will be wrong. So here we have to be patient ID and PatienD so you have to be extra cautious. Okay. And now we have to connect to the pro oh, sorry. Procedure table is connected to the encounter table. So for adding Encounter table, we have to add one more encounter table here. And we can just do it as encounter and encounter ID is ID only. Correct. I hope you guys are able to understand about data modeling, how we have done that, how we have linked fact and dimension table, and with a different key spare. So if you are the first time doing it in tabu, so this is very advanced problem that we have dealt with multiple fact relationship. So what you can do is you can just rewatch this video again to solidify knowledge, and all your doubts, you can just comment in the comment box. I'll be happy to interact with you and I'll happy to assist you on that. Next video will be dealing with how to start thinking as an analyst and how to build your KPIs in tabu. So I hope you're excited by now, so see you in the next video. 13. Data Blending in Tableau: So now tors try to understand what does data blending means. So basically, like the terms just like the data blending. So we are blending the data from different sources. So the same happen when you're working in the real time industry, so you may have data in the form of different format. You can have the data in the form of Excel or in the form of CSU file, or you can also have in the form of Google Bi Query or any SQL database, right? Or you can also data in the form of special files. So basically, we use special files like when we are doing the visualization in the map visualization and we want to go in the granual then use special files. Suppose you are doing a data blending and you are blending two data sources, and you want to set up some relationship between the two data sources, then you want to perform your analysis. Suppose you are connecting the Excel data source and one SQL database, and you want to perform your analysis, then data blending comes into picture. So I hope you are clear with the basic definition of data blending. So now let's try to understand how does data blending work in the background. And once we are familiar with that, we'll be deep diving into tabu, and we'll be performing data blending in tabu. So you will get a big picture of it. Next slide and try to understand what does data blending mean? So what happen is, so basically, you are having two different data sources, right? So suppose you have data source DS one and the other data source DS two. Okay. So these two are separate data sources. So if you want to get the information from these particular data sources, so you need to run separate query. You need to queries out, you need to write one query to extract the data from the data source one. Then you'll be getting some kind of details from the data source, what you want. The same thing you need to do with the data source too. That is the outer query will be running from the data source to to extract the information from the data source. What happened is like whenever you are queering the data source, so it will be different queries. Now you want to do the data blending in these two data sources. You need to have some linking field to link the data, the linking field can be one or the two fields or more than one field can also be there if you're performing data blending. So what happen is when the blending relationship established when you find a linking field, you'll be seeing two things in the tabu interface. The first thing is like your primary data source, like suppose, in this case, our primary data source was DS one. So it will be presented by this cylindrical icon with a blue tech on it. Okay, so this will be a primary data source. And the secondary data source will be presented via orange color. Just lend icon and then take on it. What happen is whenever you're connecting whenever you're doing blending. What happen is suppose you're doing data blending. What happen is whenever you're performing data blending, by default, it will take the left join. With your primary table, your primary table will be important table, like all the information and primary table will be conserved, and some of the information which are not available in data source two will be lost right now this is done right. Basically what happens is, if you are drawing any dimension from the primary data source, D will be shown in the table interface that will have no error. But if you drag any dimension from the secondary data source, you may see the asterisk sign. Table is not able to identify what does that dimension means. What happened in background is if you're dragging any dimension from the secondary data source, so you have performed the left join. Remember, so at the left Jen, what happens is like, suppose you have one field ID here and one ID here. You are performing left join using this ID linking field. So the ID which are in the left table will be preserved. But data, but some of the ID will be more in the secondary data source. That will be not available in the primary data source. So the primary data source doesn't have the information of that particular dimension. That's where this Aztec sign comes. So I hope you are clear about that. So we'll be seeing live in action in tabu, so don't worry if you if you have some confusion in this part. So this is how data blending works. And you can also edit the relationships. Like, suppose if you want to change the blending parameter. So the blending parameter will be this blinking field will be designed by Taboo itself. By default, table will identifier. But if you want to change, you can do that. So I hope you are clear about that. So one more thing is there, like this data blending bugs only on the sheet level. Like if you change the another sheet, so the data blending will be new for you. You can perform the data blending according to changing your primary and secondary data source. So this is worksheet level. Okay. So now let us try to see all this live in action in tab with the help of example. So let me just open the tabu interface. So suppose in this example, we are seeing the raw supplies dataset. So I'm just connecting the Row supplies dataset. This is our data source one. In this particular case, what I'm doing is I'm using my order sheet and I'm dragging to the right hand side to the tabu shelf. So once I have dragged it, so you can see it is still loading, so let us wait for a second. Okay cancel this update now. Okay, so now the dataset has been loaded, but you can see like the headers are not bright right. You can see some null values here and the column header is f2f3. So something wrong in the Excel sheet. But the tabu order this data interpreter option. So once you click on that, so it will automatically clean for you. I will identify what is the correct header for your particular dataset. So that shows the true capability of taboo once again. So once you are done with that, so now you can see all the data sources have been corrected, right? Yeah, perfect. So now what I want to do is suppose in this sheet, you can see, one more thing orders add on. So these are the orders which are add on afterwards. So one is the order sheeld that contains order of certain customers, and one is the order add on that might be added the later on, but not have been clubbed with the order sheet. But we want to see as a single sheet, right? So at that time, what we can do is we can do the union. So if we are doing Union, so the number of columns should be the same and the data data. So the number of columns should be the same and the data type should be the same. So in this particular case, I have seen that and it is same. So we can just drag this and we can drag into the orders. So when you can see the union icon. So once you've done that, you can see this type of thing like the boxes, tables or union. So now what I want to do is I want to double click on that and I want to join the order table with the returns table. This is my first data source which I'm preparing. And what I want to do is I want to preserve all the records data present in the orders table and data common in the returns table. So I hope you are clear by this. Now let us move on to sheet one. So this was my first data source, right? So first data source contain the information of orders and the returns table, the person who are ordering and who are returning to the current customer. Now let us try to connect another data source. So in the tabu interface, you can see the plus icon. So in this particular case, I'm connected with the same excess spreadsheet, but I'm connected with a different sheet. So in this particular case, what I'm doing is I bound the goal by region segment like how much goal they have achieved. So you can see in this particular dataset, we have segments, the regions, and the goals. Okay, so now once you move to sheet one, after connecting this, so you can see, there are two data sources that we have connected, right? So now to establish data blending. So what we need to do is first, we want to identify the primary data source. So in this particular case, our primary data source we want to take is the orders and datas table, right? So what we need to do is we need to drag we can drag the dimensions from the primary table because it is a primary taver so it will contain all the information, right? So what we can do is suppose I want to see the regions segment and the sales and click on Show me and I want to show in the form of table. Right. Now once I have dragged all the information, so you can see a blue tick mark has been there. So this shows like this is the primary data source. Now what I want is I want some information from the secondary data source to perform data blending. So what I want to see is I want to see the goes for different segment and region. So once I drag this into show me, so now you can see it has already calculated the value, right? And in the left hand side data pin, you can see, this has been established as a secondary data source, right? So what happened is you can see the pain icon. So this pin icon means the linking field. So to see what is the relationship that Tableau established by default. So to see that, what we can do is we can go to the data in the ribbon section and we can go to the added lend relationship. So you can see our primary data sources orders. If you want to change it, we can change it from here also. Okay, I told you we can edit the relationship if you don't like it, if our analysis is not perfect. So in the right hand side, you can see Tableau has, by default has identified regional segment as the linking field in both the particular data source because that is the same field and like the same configuration they have data. What we can say is like the datatype is same, and the value that they contain the regions will be same in the both data sources, right? So that's why identify correctly. So now let us click on Okay. So now suppose if I want to change the linking field, suppose I want to see only by region. So if I dissect this segment linking field, if I stop this, so you can see now the values are again calculated. Now it is only according to the region wise. And if I click on it again, so now the value has been changed. And if I change this thing, so now it has been talbed by region wise. But if I unclick both the pins, so it will show fields cannot be used because like I told you for data blending, we need to have some linking field. Without linking field data blending doesn't work. I hope you're clear bited. So let us turn this on. So I hope you're clear bited. So now, let us try to perform one more. What I want to do is I want to filter it by year. I can also do filter will work when you are doing data blending. Once I click on Data blending and I just selected one year, I want to see for only one year. Now you can see the SAS value having changed per year value, the good be same. So that's how databnding works. Now, let us one example. So molti one more example. Suppose this time, what I want to do is I want to see my go sheet as the primary data source. So what I can do is I can just drag the dimensions and measures from my primary data source and show in the form of tab. Right. Now what I want is I want some. So now you can see the secondary data source, like this is the linking field which these two data sources are connected, right? So suppose what I want is I want to see the customer name from the secondary data source. So if I'm dragging this customer and I'm clicking on Ad members. So you can see the star icon, so it is not able to recognized in Tableau and you can see a orange slender icon here this is the secondary data source. At that time, what happened is our primary data source was goals by region. And this doesn't contain the information of customer's name and our data is blended with the regional segment wise, it has from the left join that we have. So all the records that are preserved in the Ghost table will be preserved. But this extra details is not available, right? So that's why this data blending is showing the star icon because it has the left joint so it doesn't contain the information of all the customers in a primary data source. So Daft is not able to show that. So this mostly happen when you encounter in taboo star icon. So most of you you maybe have searched in Internet like why does this happen? So this is the reason why it happened in tabu. So I hope you're clear with this data blending spasic exercise. So this was a small video to understand about data blending. So we'll see you in the next video. 14. Understanding Join Concepts: Welcome back. So in this particular video, what we'll try to do is we just try to see one more data modeling concept that is joins. Okay, so now since we have seen relationship, data blending and now joins, so the thing is like you have to be cautious. I will just suggest one thing like use relationship, like if you can, otherwise, use join. Otherwise, then use data blending because the thing is like it impact the performance wise. So the thing is, first thing is, if you're using a relationship, so what will happen is, it will be much more faster because, like, the it is happening in the logical ear. So all the table will be intact, like different with each other. Only the thing is it will be connected to some primary key or some kind of keys. Okay. But if you do joins, then what will happen is like it will create on physical table out of two different tables or three different tables. And the thing is like it can happen like it may lead to some kind of duplicay and you have to use fixed level of detail expressions to solve that issues. So if you like, increase the number of melodies in taboo, that also can hamper performance in some kind of extent. So this is one of the point to remember you can remember. Okay. So now let us just move on to the joins concept first. So the thing is, for example, we have two table given, okay. This ID one, this table, we have one, one, one, two, three, 33, and table two, we have one, one, two, two, four, okay. So what I want is I want to show you how you can see how the inner join, left join, right join for uto joint work. Okay. So the thing is inner join mean, like only the common decors from the both the table will be preserved. Okay. So if I want to do inner join in this, so only the common record will be preserved, and this is known as destructive join, so you have to do it cautiously, if you can lose some kind of information also, if you have inner table, okay. So for example, we have to do inner join. So how you can do that, you can see this is one. So this one will connect to these 21 because it is matching record. So if you give me two rows, then this one will match with these two record, two rows. This one will match with these two. Two rows. Then the two will match with these two record two row. Okay. Now comes with a three value, so you can see value doesn't exist in table two. Okay. So we'll not have any record for the 31. Then again, no record. Then again, three, no record. Okay. So if I sum it up, so you can see, I'll get a total of eight records if I do inner join. Okay. So now if I want to verify this, so I can just go back to my tabu. So you can see I two tables. So one is like the table one. So this is the table two. Okay, so now let me just do the join operation in that. So how you can do that, just go to Table one, that you are valid. Drag it to right hand side, and this is the logical layer. So double click on it and just go to table two and just drag it to the right hand side. Then you can see a vein diagram. So it will show left join, right join, full autojoin. So at this now I'm doing inner join, so it will give me common records. So you can see the bones connected to one. Then you can see if you count a record. Then you can see it is a total of eight chordite, one, two, three, four, five, six, seven, eight right. So our logic was correct, how we build. Okay. So now let us see how left join work. So left join wheel means it will preserve all the left table records. Okay. So at the common records. So you can see this is the one. So one will join with these two, so two records. This one will join with these two, two records. This one will join with these two, two records. This one will join with these two, two records. Okay. So now since it has a left join, so that means we also preserve the common element plus as well as the left element. So three doesn't present in the second table, but it will be preserved. So it'll be one row, then three will give me one row. Three will give me one row. Okay. And it will be paired with a null or not defined value. Okay. So you can see if I add this up, so it come out to be 11, so eight plus three chords. Okay, so it will be like 11 records. So let me just verify that. So if I do a left join. So now we can see we have additionally got the three values here, and it is better than null Very side. So our logic was correct. Okay. So now let's just see for the right join. So for right join, if I do, so if I just remove this, so the trouble is this one and I want to do a right join. So that means like I have to take the precedence. I have to pres up all the record in the second table. And then common record from both the table. Okay. So I'll just go from this table now. So you can see this one will pair with the three record. Okay, this one will pair with the three chord. These two will pair with one record. This two will pair with one record, right. And this four doesn't available in this table, but it will be preserved, and this will be also preserved. So if you count this total number, so it is like a ten. So you got ten rows, and you will get four and null should be paired with null values. Okay. So if I do a right join, Okay, perfect. So now you can see four NL. And if you count one, two, three, four, five, six, seven, eight, nine, ten, right. So our logic that we are building that is correct ite. So now what do you do for the full out or join. So full join, what will happen will pis up all the records. So eight from the left for the inner join. Then the left table, like how many records were added. So left table like we have three records, so three records were added. And then the right table, we have two records that were dit, like four null. So if I add this, it'll be hurting, so it should give me hurting records. So if I do full outer join. So if I do across, then you can see it is doing the same thing, right? Th in rows. So we are logically correct, okay. So I hope you are able to understand this concept. So now let's do the same practice for these two table. But the challenge here is we have to null the cost and introduce, Okay? So why I'm teaching this way is because this may be a good practice to understand joins. Like if I take the real world example, if I take any tables, then you may do it very easily with a table seeing view. But, you have to understand the logic first. Like, if you're able to understand the logic, then you can play this logic in any of the table that is given to you. Okay. So now let us just do for this table thing. So, for example, I give this as ID and ID field. Okay. And I just give this table three and table four, okay. And let me just load it. So I just do Control C, and I can just do I can just cross this. I can just give Control V. Okay, this will paged it. Just remove this no need to worry about this. I can just give this rename as table three. Okay. And same thing I can do for table four. Okay. So we'll do pal side by side. So it'll be a good practice for you. Just Control V. And rename. And table four. Okay, remove this. Remove this. Okay. I was at table three. Okay. And I was at table four. Okay. Perfect. So now suppose if I want to do inner join. Okay. So what will the number of record? So what I will do is I will just ask you to pause the video and just do it by yourself once and then come back to the video and then we'll do parle. Okay, so let's go ahead. So suppose if I do inner join, what will happen is so this is the primary table. So this one will match with these three records, right, to three records. This one will match with three records, three, this one also three. This one also three. This one also three. This one also three, though you might be thinking like this null is matching with this null, Okay because it's a common record. But just let me make sure, whenever you see nullcord, so dead null can have different meaning. Okay, so that null operators are never equal, you can say. Like in this table, this null can mean 0.5. And this null can mean 0.2 if we give any value to it, okay? So nulls cannot be same anytime. Okay. So these nulls are not the same. Okay. So it will give zero. I will give zero. Okay, so that is the caution you have to make sure. So suppose you have any table in your dataset given to you and they have null if you do the inner joins, so the null decor will not get matched up because that null may be different. So that you need to understand. If I do the sum up, so you can see 18, so it will give me 18 records. If I do the same thing in tabu now, remove this, double click on this, at table four and do inner join. If I see you can see 18 records have been there, so we are doing correctly. So if I do left join, same till this part, and these two null will have different record. I'll be 18 plus two, 20 records. Okay, so let me just check that. If I do left join, perfect, 20 rows. And if I do right join, then it'll be 18 record the same. And then we have null record here and two here. So two records will be added from here. So 20 records. If I do join as well. So you can see it is 20. Perfect. Now if I do the full outer join, then 18 record from the inner join and two record from the left join and two record from the outer join or right join. So it should give me 22 records. So perfect its 22. So I hope you are able to understand the different concepts like how it is working in backend. So that is a major thing to understand. Same thing you can apply to real world case study. So I go to my dashboard and go to MG 16. And if I go to Super Sampa Superstore and go to datasource, I suppose if I want to club orders and returns table. So if I view the data, so you can see at the order ID that is common. Okay. So what I can do is I can just double click on it and I can just drag this return table. So now you can see the operation, how you want to do. You want to preserve all the records data. You want to preserve all the returns data. You want to have full Auto join Like if you don't have order ID that is not return, that also you want. So that may a duplicaty thing. So as of now, I can do afjoin, okay? This is how to think about it, which kind of join you should use in which kind of scenario. So I hope you're able to understand the join concept. So see you in the next 15. Calculations in Tableau 01: Calculated Fields: Now in this particular video, we'll just see how we can create calculations in Tableu. We'll just see how to create simple calculations. Then we'll see how to create a level of digital expressions and how to create table calculations in tabu. Okay. So we'll just start with a basic table calculation, a basic calculation first not table calculation. Okay. So the first thing is we'll be connecting to the sample superstore data set, for your understanding, just go to datasource and remove these people and return table. So only I want the table is that is the orders table, okay. So in the order table, you can see, uh, we have the data related to the orders the patient is the customer is making and we have the main KPI profit, the sales is going in the quantity. Okay. So now what I want is, for example, I have my subcategory, if I drag it to the row shelf and I have my profit to the tax shelf. Okay. So now you can see some are negative, some are positive, right? So what I want is I want to show, which of the subcategory are profitable or non profitable, right? So in that case, we have to create some kind of calculation, because we don't have any field that say like this is profitable and nonprofitable, right? So in order to create a calculation in Tableau, there's an option. You can see after the filter icon, you can see this drop down. Click on this, create calculated field. So a pop up will come up like this. Okay. So this pop up is where you can write all your logic here, and this is the calculation name you can give. And if you click on this arrow, you can see all the functions available if you're learning new. So suppose if I want to write any date function, date difference, so you can see you can write date part, start date, and date, so this will return the difference, and you can also see the example. So how cool is that trite? So the first thing I will just do is I will just create a calculation for profitability. Okay. I can just rename it profitability. Okay. So I can just write INS statement. So and then we have to write whenever we're writing IN statement. So if my sum of profit, okay, is greater than zero, greater than equal to zero, then I want to give the taxes profitable. Okay, else I want to give it as a non profitable. Okay, I can give and and click on Apply, click on Okay, and drag this to the row Self. Perfect. So now you can see how cool is that tight. You can see the ones which are going negative, like less than zero, that are showing non profitable t. So we have created one calculations. So now the thing is, you can ask what all we can give in calculation, right? So whenever you're creating a calculation, so you can use any dimensions if you want to use you can add any of the measure if you want to use. You can add the parameters if you want to use. You can also add some kind of text to it. You can also add some kind of function to it if you want to add, upper function or date function, some kind of function, or plus, you can also add the commands. So if you want to do command, is this. Okay, so as of now, this will give me calculation error, just wanted to show you but all we can use in calculation. So there's no abundance of choices. Okay, we can use. Now the thing is we have created this. Okay. So now what I want is I want to show state wise, what is the profitable and nonprofitable states. Okay. So I can just create the next sheet and for creating the map visualization, what you can do is first of all, just write a profit by state. You can do is you double click on the state thing, double click on the state, if it is tag to geographical equation, you can see Blu icon is there. So that means like it is tag to the geographical thing, double click on it. You can see the point will appear and just change this automatic to mark shelf. Okay. Now what I want is, I want to change the color code. So color coding, I can give in the color shelf. So if I want to change the color, according to profitability, I can just drag it to the color shelf. You can see there are most of the country that are profitable, so I can just change the color code. So profitable, I want to give green, non profitable, I want to give gray. Okay, apply. Perfect. So you can see the not gray. I can just give it as a red. Okay. Perfect. And I can just add the state as a label. Okay, so you can see taxes, Oregon, Pennsylvania, going on losses, non profitable, and Mexico, California going on profit, right? So this all we can see from this graph, right? So I can just give them as profitability. Okay, I can just duplicate this. Now I want to see only profit, okay? So I can just do profit. And instead of profitability, I can just add a profit measure. So it will show me the exact figures. Okay, so you can see California is going on profit and taxes going on losses. And you can also the figure number, right? So I can just click on this added button and change it to be a red gray diverging. So let me just check diverging. Okay. Apply. Okay. Perfect. Now thing is we can also clean this up we only want a US map. I don't want this outer line. Okay. So what we can do is just right click on this. You have an option for map option. So click on this, you can also reduce this Zoom icon if you want to don't show anything. Plus, you can also go to background layers, you can just use the washout to be 100%, so it will remove all the unnecessary noise Okay. So now it's looking perfect, right? So now, for example, I will just go to one other sheet. So let's just see how we can create some more kind of calculations. So for example, you have to see the customer name. So if I drag this customer name to right hand side. You can see as if now the first name and last name are interlink What I want is I only want a first name and the last name to be separate. So how to do so. In order to do so, you can use some calculations. But tabu also offer some kind of calculation you can do easily. If I click on this drop down, you can see an option for transform. And you see an option for custom split. So if I click on this, I can give the delimiter I want to split with. So as if now, in this case, my split will be on the base of spaces, so I just give space here, spacebar and I want all element and click on Okay. So you can see the three calculations been made by tableau. So I can just drag it to right hand side. You can see Aaron Bugman and some people may have three names. You can see for this name, Mark Van Hoof. It is three names, so that's why it's popping up. If I see one of the calculation, I did it. You can see Ws use a split function. Split function, the customer name, and this is on one space, I have to return the element. You can also see here, the structure, like how we can we split statement. Okay. So now suppose, for example, this customer name is not given to us and we have been given first name, last name and th name, and I want to club all those, right. So what we can do is like if you're aware of Excel, we can concatenate. Same thing we can do in Tableau. So I can just create one calculated field. I can just write full name. I can just use custom and split one. I can just drag this into simple calculation box, plus two club it. Then space plus a second plus space. Plus last thing. Okay. And if I click on apply, click on Okay and drag this so you can see now the full name is appearing AR. We can also make some tweaks, edit this. Suppose in the first name I only want a first initial. You can see this function here. If I click string function, you can see so many function if I see the left function. So what it does is if I give left calculation coma four, it will give me the first four digit, starting from C. Okay. So the same thing I will do for this one, left culture one, I want only the first initial one. Then I want to give it a a Budge Man, and I also want to give some space. So I'm just doing that and click on Apply and there's some error. So I have given two plus sign, so just remove this, click on Apply. Perfect. Now you can see Aaron Bugman a dot Bugman Adrianne a dot N. That's how you can do the customization if you want, right? I hope you're getting the point how we can do calculations. So I'm just sharing it. Okay. Calculation. I can just save it. Okay. So now, for example, let me just see like for example, if the order is placed, okay. So we will be associating with the order ID, right? So the order ID will be having some kind of order date, like you have made the order, place tight, so order date, and I change it to exact date and I change it to discrete. Okay. And it also at the shipment date. So same thing, exact date. And discrete. Okay. Now what I'm interested in knowing is how much time it is taking to shape one order, right? So that might be the main KPI, you can look into, right. So in that case, we can create one calculated field and days to shape, I can just cite it. And I'll just crite Dadif I'm using the date dif function. So how to write data function can just go to write inside, date, day diff and you can see how I have to write. Okay. So I'll just go one by one. Date day five to write. Then I took the date part. So I want to calculate day level information. So I'll just write day in small letter. Then the first date, like the order placed and the shipment date. So what it will do is it will just subtract shipment date minus order date to give me date difference in days. Okay. Click on apply, click on Okay, and I can just double click on it. So it just give me total days. I can just change it to average because average would be the correct measure to find out the average number of days it is taking, right. So this is how we have calculated. So now what I want is I want to show in a map visualization, like what is the average day, so I can see the trend, right. So I can just go back to my chart, duplicate this. Go back to thing, and I can just write shipping days by state. Okay. And now what I can do is I can just use the filter icon to filter my calculations that I've created, and I can just use these days to ship to color shells and change it to average, right, and change the color palette to red green diverging. Apply. Okay. So I can just edit this and do it at reverse order because if it is taking more days, that means that is an alarming stage right. We should highlight with the red color. So apply and click on. Okay. So now what I can do is I can also split it. As of now it is giving the most in profit, but I want to split on the basis of good average and bad services. Okay. So if the user have this demand, so what we can do is we can write again calculation. Okay. So I can just create one calculate field. I can just write a shipment shipment service on mark. Okay. And what I can do this I can just say INS statement. So to be a plus add on to revise your INS statement, so I can just use average days. So if my average days, you can see the starting point is 2.87, it is taking minimum time. So if it is greater than two, if it is greater than equal to two, and Less than equal to three. Less than equal to four days. Okay, two to four days it is taking. Then I will say, my service is good. Okay. As I can just reduce this size and deduce this and copy this same thing. As it is more than four days. Okay, I can just not include this. Me than four days and less than five days. Okay. Then it is average. Service. As it is a bad service if it is taking more than five days to ship and order. Okay. Okay. And I can just add some space here. So now my calculation is valid. Click on apply, click on Okay, and drag the shipment service to Color Self. Okay now you can see a variation right. So if I change the color, a service with a yellow color. Bad service with a red color and good with a green color. Okay. So you can see Texas California is having good services as second time, but most of the companies are also taking more than four days to shape an order, right? So, the company can investigate into logistic thing why count some states are taking more time as usual, like than other countries. Okay. So that is another good statistics you can take a control of. So I hope you are able to understand how we can get calculations in tabu. So now what we'll do is in the next video, we'll see how to create table calculations in tabu, and what is table calculation exactly. Okay, so see you in the next one. H 16. Parameters in Tableau: So, welcome back. So now we have understood about the calculation thing, right? So before deep diving into table calculations and loud, let us just understand one more thing that is known as parameters. So the thing is like parameters are the ones, which add dynamic thing to your dashboard. So parameters are a thing suppose you've created a dashboard and you want to do something dynamic so at your user will be happy with you, they can have more flexibility in the dashboard. So that time, we can use the help of parameter. So for example, like what we can do is, for example, like, let me just do one example. So for example, in this chart, you can see it is like profit by state so what I want is I want the user to get a parameter option where they can select sales profit and quantity. And according to the selection, it should change the color, on the basis of the parameters selected. So that means like you are giving the flexibility to the user to selectether profit, either sales, either quantity to do the color thing, right? So you're doing all thing dynamic. So how to create parameters, you can just click on this drop down. Okay, create one parameter. So it would look like this. So you can just name parameter, like select measure. Okay. And you can give it the integer and you can give list and you can just give the thing like one. Two, and three. Okay. So one is like your sales. Okay. The second is you want profit, right? So I can give profit. And three, I can give quantity, right? Or I can give profit ratio. For example, I don't want quantity, I want profit ratio. Okay. So you have done this measure. So now the thing is you have to click on Okay. So only thing you have to be remember is if I click at it. You can see either you can give integer value, either you can give string value you can give you can give SAS to SAS profit to profit, you can just write it. But why I'm using integer because integer will whenever we create a dashboard. So if you use integer calculation more, so it will be like adding as a plus point to increase the performance of the dashboard. Okay. Because like integer, runs faster operation as compared to string operations in Tableau. Okay. So just a point to remember here. So now I'll click on Okay and I can just show the parameter. Click on drop down. Show parameter. Okay. So you can see if I'm clicking on profit, I'm clicking on Pfitation, nothing is happening. Okay. So there is, as of now, this parameter is not wired up. So what we have to do is when you're creating a parameter, we have to wire it up and to wiring it up, we have to create a calculation. Okay, so create again one more calculation. And what you can do is you can just cite selected measure, by user. Okay, I'm just giving this calculation as if now. So what now you have to do is you have to write as statement. So give you guys a brief, how to write a Kase statement. The thing is what you have to do is just add Ks and then space. Then you have to write a parameter name, then you have to write when and then a statement, when and then the and then and then and within and clause. This is the basic structure of the case statement whenever you're writing. Okay. So in this case, my parameters lack measure. So I've written case statement, then select measure. Then I have to give conditions. As it now I have to choose integers so it will be easy for me when the user select one, that means I have to use the sales. I have to give the sales measure here. When the users lack two, then I want to give profit measure. But when the user give three, then I want to select the profit ratio. Okay. Perfect. So now you can see the calculation is having some errors. So let me just click on this, cannot mix aggregated non aggregated, right? So what we have to do is we have to give the aggregation how we want to aggregate. So I have to give sum of sales. I have to give sum of profit. Okay. And I have to give some of profit ratio. Okay. Or profit ratio, I think, uh sales some of profit did more sales. So if we don't give aggregation, so it is perfectly fine. If I give, I think then it will show an error. So let me just re verify it at once. Yeah. Perfect. Okay. So now what we can do is click on Apply, click on Okay. Okay, so now instead of profit, just change this parameter measure you've created. So if I click on, drag this out. So as if no like this color coding will go away, but we can sort this out. So now you can see if I click profit, it is changing. Profit ratio, it is changing and sales it is changing, right. Only thing is, I have to give the color code. So for sales, I want to show the orange light. Okay. And for profit, I can give, okay, I have to give the same thing because it is the same measure. So for everything, I will just use a red black diverging palette as of now. So that is like red black diverging apply. Perfect. So now if I see SA, you can see the sales number. If I see profit, you can see profit number. If I see profit ratio, you can see profite number. So you can see we have done the dynamic thing. Okay, so that is how we can use the parameter. So let me just show you some more use case or parameter. So for example, let me just put order it here. And put sales here. Okay. And I want to do it for each month level, okay? So just select the month here. Okay. So now what I want is I want to select the start date and end date using the parameter and give the sales value according to data range. Okay. So how I can do that. Okay. So the first thing is we have to create two parameter for start date and end date, right? So create a parameter and just select start date, and you can give the data type as date, and give all as it is. And then what you can do is you can just duplicate the calculation, edit it, and now you can give this is the end date. Okay, apply. Okay, so start date and end date you have given. Okay. Now what you can do is you can just show the parameter, show the parameter. Okay. Now what we can do is we can just go to Analytics step and we can enter reference line. So a reference line as of now. And what I want is I want to do it for the month or date, so I can select that. And now you can see an option for start date and end date, right? So I can just select the start date. And instead of line, I can just do the bend. So it just for the two lines. So the start line, I want to give the start date. And the second line, I want to give the end date. Okay. End date. Perfect. Okay. And Phil, I want to give it as a lighter shade of gray. Okay, and click on. Okay. Perfect. Now suppose if I select any date range, suppose if I select from first tugs. Okay. What I do is I just go to 2021. Okay. 2021. Okay. So from first daggers, 2021, I want to select from Fager sorry. And I want to show till, for example, January of 31st. Okay. So you can see the reference band has been created tight. We can also adjust the formatting. Solicon formatting, I can give the alignment. I want to give it as a upper align or middle align, I can give that. Okay. So I'm just giving as a top line as of now. Perfect. So now you can see the range right. So now what I want is I want to give the sales value, what are the range the user is selecting, I want to give the total sales value, what is done in this entire range. Okay. So how to do so. So the thing is like we have created a parameter, but thing is that we have to wire it up, right what we can do is we can just create a calculated field and we can just give sales in range. Okay. So what I can give is like if my order date is greater than equal to start date, and ordered it is less than equal to end date. If this condition is true, then I want to give my sales number and then apply, Okay, and just give this in detail. Now what I can do is I can just go Sheet 18 and I can just write SAS for the selected range. Okay. I can just at start date. And date. Okay, and I can just get the calculation that I've done. Okay, apply. Perfect. Okay. So now you can see what it is doing is. It is just giving me says for the selected digion for this and this is this much okay. So I will just clean this bit out. So for the date range between this and this. Okay. And what I will do is I just undo it a little bit 11 size and bold it. Okay. Click on Apply. Clicono. So now the thing is as if not it is showing me the ranges. So you can see the range is like from 11,000 is the minimum one. So if I go down, so 11,009 foot one is the lowest one, and the highest one is like 97,502. So it just give me a minimum maximum range. So what I want is I want a total value between this range, okay? So what you can do is you can just go to the calculation, and you have one function known as total. So it the total function inside it. So what it will do is it will just calculate the total value. Like what is the total sum of sales, okay? For the entire range that is selected. So it's a table calculation, so I can just close into total and write a sum. And click on Okay. So apply. Perfect. No need to worry. So just drag Sing again in Dt shelf, and now just select it again in the text title. Okay. It I've just the wrong thing. So just let the sales in range and click on apply. Click on. Okay. So now you can see after applying the total function, it is giving the aggregated value, but that is a total of the value that is selected in the entire range. So how I can verify this is so I can just elect for one year or one month. So first August, I can just change it to 2021 and change to Agurs. Okay. So this is for entire range. Okay. So first tags to 31st ags, it is like 28,000. Okay. So I will just duplicate this. Okay, I will just duplicate this as a cross step. And if I see the value for August 2021, so it is 28,918. Okay. So now you can cross verify that the number it is showing is correct. Okay. So this is another way you can just revalidate by creating a cross step. Okay, so I can just write sales in range. Okay, parameter. Okay, so I hope you were able to understand this, and it was a bit more intuitive way you have seen now. So this is why we use parameter, like to add dynamic thing, like to add interactivity to our reports, we can use parameters. Okay. So I hope like you were able to understand about the parameter thing, and we'll be using parameter like wherever we can, in the case study that we're trying to solve in the upcoming videos. So now the thing is, like, let me just introduce you to the one more thing that is like table calculations and AUD, right? So what we'll do is, we'll just clear this sheet. So what we'll do is like in the next video, we'll just cover how to use table calculation, the basics way and the level of data expression. So it'll be like handy when we deep dive into the case study. 17. Calculations in Tableau 02: LOD & Table Calculations: Come back. Now since we have seen the calculations and parameters like how to use and when to use parameters. So now let's just move on to some different kind of calculation. So that is known as table calculations and Ads. So we'll just go with the table calculation first. So for example, let me just check for the segment first. So we have different segments. So if I drag the segments to the row shelf, and if I check the category to the column shelf. Okay. So now what I want is I want to see CS of first. So just I'm dragging the Ss, double click on it to the roo sheelf and I'm just going to the analytics stab and adding the totals. Okay. So now you just see how does table calculation work and what you should be cautious when using table calculation. Okay. So suppose you're making any table or any visualization, and in the visualization or in any table, you are using table calculation. Okay. So it is very simple to apply that, so you can just click on this drop down. You see an option for quick table calculation, and you can add some of the calculations are pre built, so you can use running total to see the cumulative sum. You can see the difference, percent difference, percentage total, ranking, percentile or moving average. Okay. So in this case, what I want to do is I want to calculate the percentage of total, okay. So if I click on that, so just see how the percentage of total is calculating. So as of now, you can see the percentage of total is calculating from left to right. Okay. And it is calculating for the consumer section, it is calculating for furniture. How much is the percentage for office supplies? How much is the percentage Ss and then adding up to 100%. And same for other segment right. So the thing is you have to make sure the two thing. One thing is like the calculation you're using, table calculation you're using. Second thing, the direction you are doing the calculation. Okay. So how to check the direction, you can just click on this drop down. You see an option for computer using or you can click Editable calculation. Okay. So there are mainly three ways, three ways one is table, one is pain, and one is cell. Okay. So as of now in this, the pain is not there, but I will show you like what does pain mean? So the thing is like how you want to do your calculation. So one is like table across. Across means left to right, table down. Table down means top to bottom. And cell means for the individual level, you want to calculate. Okay, or in special dimension, you can do. So for example, I'm doing table across over sum is happening 200% through here, okay? So if I do table down, so what will happen is for furniture category, it will check, like, how much is consumer, how much is codpit, how much is home office is making. So it will change the scope of the calculation. So if I do table down, you just see the hundred percent. So you can see now the table is now the calculation is like, for the column level. Okay. For each category level, it is calbrating. Okay. And if I do cell level, then it'll be 100% for each individual cell, but this is not a correct direction, right. So I will just do as if not table across. Okay. Um so this is one of the ways. So now the thing is, if I change any dimension of measure, so it will change the calculation. So if I change the category to row shelf, so now you can see the scope has changed, okay. So now I a clicon is drop down, a table calculation, now you can see it is during table across. But a table is like all the dimensions are in the column way right. So we cannot do column B. So if I left to right. So what will happen is like it is catching furniture, consume it is like one cell. So it is doing cell level calculation. That is 100%. Okay. So in this case, we have to do either table down. So in table down od happiness. So if I click on analytics and added subtotals. So now you can see what it is doing. It is checking for furniture, like the tal is 32 percentage, office supplies is 31. Technology is at 36, and it is divided into different segment and then summing up to 100. Okay. So this is like table level. Okay. So now what mean is like pain level, I told you in the starting so pain means, you can see, we have added two dimensions. So this furniture is like one pain you can save. Inside furniture, we have different segment, and then inside office supplies you have different segment. If I want to see for one pain at one level, so what I can do is I can just do pain down. So now this calculation will be calculated for single pain level. So you can see the furniture. The total is 100%. And from this 100%, like, how much is consumer section, how much is home office, how much is corporate? It is calculating. You can see consumer and cooperates the leading subcategories or this segment you can say. And the same is for the office supplies and the same is for the technology. So this is how you can do calculation. So I hope you're able to understand how to do table calculations in taboo. So what I would advise you to, like, you can just play around. So what you can do is you can just play around with some of the plating tables and doing table calculation. So it will be a good way to practice. Okay. So now what I will do is I just clad on sheet one. And what I want to do is, like, for example, I want to see the moving average. Okay. Moving average means, like, Oh, before age, I want to see the cumulative thing, okay. Cumulative sales. Okay. So what I can do is I have to drag the order date first, and then I have to direct the sales, right. And sales I have to drag into the root shelf. And then what I want to do is I want to see all the months in here. So I can just click on this drop down, click on month so I can see shrew me for a full timeline, right. But as you know, this is the exact value the sales is making in September 2021, this was a sales number, okay? What I'm interested is I'm interested in knowing, what is the cumulative value? Cumulative, like how year over year, the cumulative um is. So cumulative means like you're adding up the entire for the starting year to the last year, okay? So what I can do is I can just click this drop down, Control click and create one more pill. And in this I can just click on the dropdown, quick table calculation, and I can just a running total. Okay, so this is the run in total. For you can say for the entire, line that we have for the Superstore. And what I can do here is I can just add four different segment I want to see, so I can just add the colors here. Okay. So you can see for the segments like this is the community one. And what I can do is I can just add this Control click and add it to labels. And instead of string all the labels, I can just click on this drop down and click on nine end and only at the end of the line, I want to see the sales. And I can just click on the format thing, and I can just change it to $1. So currency custom and I can just change it to dollar, and I can change it to thousands. Okay, and I can just make it to one place one. Okay? So you can see the consumer section is the most making sales. Like the cumulative is like 1171 k and 7.6, falling by corporate section. So consumer and corporate are the leading section home office is lesser sale as compared to these two sessions. Okay. So now what we can do is we can also add more table calculations. So suppose, for example, I can Control click and it here. So what I can see is I can also see the trend, like how it is going the moving average, you can see. So what does moving average means is? So moving average can see the trends, the inside pattern you can see, you can see, like the granularity we can see, like how the moving algees going on for like six months or 12 months. So that will show us if the trend is going positive or negative in our dataset. Okay. So how to do so we can just click on this dropdown. Quick table calculation. And we can just add as a moving average. Okay. So now, as of now it is if I click on this drop down and click Additable calculation. So you can see moving average is asking me how you want to do the moving average. So it is ticking from the previous two values and the next value. That is a current value. I'm selected. So it is moving like three months average, you can say. So what I can do is I can do it for six months or 11 months. So if I increase the numbers, what will happen is the line will go smooth. Okay. So this is just like exponential smoothing, you can say. So now if I click on Cross, so this is that point. So now what I can do is I can just drag this last one to the end side. And these two, I can just do a Duexis, so I can just club it, so I can just click on the Duexis thing. Okay. And I can just synchronize the axis, click on this synchronize axis. Okay. So now you can see the correct trend how it is going on. So now it is much more you can say can't use that. Show. It's much more intuitive, you can say. Okay. So now the thing is, like, you have learned how to do calculations, how to use table calculations, and how to, like, create like dual Schar in different kinds of chart, right. So now the thing is we have also on parameter thing, okay? So what we can do is for moving average, like you started saw, like we were giving the manual number, like six months or, like, 12 months, right? So what we can do is we can also just, uh, Duta parameterized. So I can just create one calculation field and I can just drag this last field, not this last field. This is for the running sum. So what I can do is I can just drag the moving average just like the second calculation, I can just drag this. So this here, I'm giving the number. Okay? So what I can do is I can just create one parameter to wire this up. So what I can do, I can just write a moving average sales. Okay. Apply. And instead of that, I can just drag this above this. Okay. Now what I can do is I can just create one parameter and just give select and months to change the moving average. Okay. And as you now I want to give the integer value and I want to give the range. So minimum moving average I want is for six months, and the user can see up to or you can say 12 months or 24 months. Okay. So click on Okay and just show the parameter. But as of now, if I change, so you can see nothing is changing because we have to wire it upright. So think is I have to go back to my calculation and just like my moving average sales, add this instead of 11, I can just write minus so you have minus because you have to go like you have to see for Muga for previous months, right. So I have to give minus sign. That time month to travel. Ligon apply. Icon, okay. So this is for six months. So if I do seven month, eight month, nine month, ten months, you can see that it is then variety right. And user can see that trend, according to the wish. So now we have implemented all the things in a one go hide right. So I hope you are enjoying it and you have learned something from it. So now let us just move on to the last Topic of this video. So we'll just see like the allods. So in this course, there is no scope to cover the Adis in advanced session because this scope level is not related to the advanced tabu. So we'll be covering in the later part of the taboo course, but we'll try to use that concept in the case study like wherever possible. So now I just see how to write AOD. So I can just clic on create Cal credit field. And to write AOD, there's a pattern. So what you have to do is size CL basis. And in the CL basis, up to give the allody name and the dimension, and then colon and then measure. You want to do the aggregation and you have to aggregate it. Okay, so this is a pattern. Okay. Now the thing is, like, there are three types of Odis. Okay. One is fixed. So fixed means you are fixing it against some dimension and you're calculating some value. So we'll just see live in action, so you don't have to worry, include, exclude. Okay, these three other Audis, and this dimension thing is not necessary to give if you don't give, so it will see for the entire dataset and calbrate. Okay. And then the thing is like your measure should be aggregated every time. So this is how we write. Okay. So let us see how to write Audi. So I will just name this calculation as category By sales. And what I have to do is I have to just write fixed first and then category. And then I want to do aggregation. I'll just lose some of sales. Okay. And click on Apply under score 01. Okay. So apply. Okay. Perfect. So now you can see if I am entering, if I add category. Okay, in my visual and subcategory, and if I show the sales number. Okay, so there is no way to show for the category by sight. So now since we have calculated the calculation, so what I can do is I can just drag this to the tax shelf. Or what I can do is I can just double click it. So now you can see so now you can see it is calculating for the entire category. So if I sum this up, so this will be the same number that each category is making, right. So this is the power of Audis, you can say. So now suppose, for example, in the visual, like in the table pane, like, we don't have region. Okay. But what I want is I want to see for the region sales. Okay. So what I can do is I can use Audi, so I can cite regional y sales. Okay. And I can just use this time, I have to include some dimensions. I have to write include and region, and I have to give sum of sales. Okay. I can also do any other sales if I want to see average sales by region, so I can also do that. So let us just do average this time. Click on apply click on Okay and double click on it. Okay, so this is the regional average regions by this. So how to cross valifie I can just duplicate this and I can just clean this up. And now what I can do is I can just add the region thing. Okay. And I can just add a series value. Okay. Now what I can do is I can just check for bookcases, for example. Okay, I want to do it average, so just change it to average. And for subcategory bookcases, I can just filter it out. Bookcases, apply. Okay. So you can see for bookcases. For all the region, the sale is around 1,926.2. Okay. So forgo already 1926. Okay. So we rounded it off, but it'll be like the exact value, if I change the format thing. And if I change it to number custom, I can see now is 0.20, right? So it is a correct number. So now you have learned how to use AOD. And the same thing we can go for the exclude AOD, if I want to exclude some dimension. Okay, let me just show you like one more use case of AOD. So for instance, I've created one AOD or name. So what I can do is like, for example, I want to see for each customer name if I add all customer name but other order dates like they have buyed from us. Okay. So if I click on this drop down and if I click on or measure, and if I click on minimum date. Okay. So now you can see this giving me the minimum order date for the particular customer. Okay. But if I remove this dimension from this, then it will all the information will be gone, right. So now, in order to fix that, what we can do is, I can just write a level of digale expression. I can just write one calculated field. I can just write customer name, first purchase date. Okay. And I can just fix it, fix that customer level. Okay, and I can just write minimum of all date, and I can just click on Apply click on Okay and double click on it. Just it right inside and do it as a exact date and change it to discrete. Okay. So now if I move this and if I move this customer name, then also you can see all the related information is available. So all customers have purchased at different dates, so that information is not lost right because they fix that customer level, so it is calcrating at customer level only. As if now the customer is not there, but it is showing all the rates that you have calculated. Okay. So now the thing is like this is the first order date that the customer has placed. Now the thing is like if I place the order date again, okay, in my lookup table. So now, for example, if I put the order date again to verify my mini model data is correcting. So if I click on that and clicon discrete and click on exact date and Klicon discrete. Okay. And if I drag it to left hand side. Okay. So you can see the Aaron Bergman has made the order 18th, the seventh, March the tenth of no, right. And the first customer date is 18th of February. And same for Aaron Hawkins, so our calculation is working correct. Okay. So now the thing is suppose, for example, you have to find out a second purchase date, like how the customer is bringing second purchase. So for Dad, what we can do is we can again use calculated field, so I can just write a customer second purchase date. Okay. And what I can do is I can again fix that customer level. Okay. And what I can do is like if my customer first date that we've calculated. Okay. Is less than. Is less than. A date. Okay, so if my ad date is greater than the first purchase date, right? So then I want to give the A date, right? And what I can do is I can just write and, and what I can do is I can just flos inside a minimum because I want the minimum of order date, right? We have to give an aggregation. So I can just close this and click on apply and just check it out. L if our calculation is working fine, go to calculation and just cite second purchase date to the right hand side. And just do it exact date, and again, change it to discrete. Okay. So I can see for Ambach is like seventh of March. For this is 13th of My then 28 March, right. So it is calculating correctly, right? So this is how when you have to use label of data expression, like when you're going into entire granularity of a dataset, and you have to explore or find out some dates or some kind of value like output data, then you have to use this fixed level of data expression. Okay, so I hope like I was able to, like, make you aware about the TBA calculations, ODs, and the parameters thing. Okay. So now what we'll do is, we'll just see in the next video and start building a KPHR in a dashboard. So see you in the next video. 18. Tableau Order of Operation-Filters Flow: Welcome back. So now is the perfect time to introduce you to the order of operation in Tableau. So basically, there are six filters, you can see this original documentation. So there are six filters in Tableau, and this is the order they work in. So the thing is, these are the operation on the right hand side, okay? So you can see we have fixed level of data expression, include exclude, table calculation, trandline what happens is like this Fix AUD follows context filter, data source filter, and extract filter. You have to read like this. So the thing is, if I put dimension filter, so fixed Aoty will not get affected, so it will not change the value. Okay. And the same thing, suppose you have any table calcuation and you try to put table calculation filter there, so it will not be impacted because it follow above this rule and below this rule, it doesn't follow. Basically, above this line, whatever these conditions are there, this will be active and below this line, this will be inactive. So this is the way you can read it. So let me just go one by one and tell you how to create filters. So the first filter is Etag filter. Okay. So for creating Etag filter, just go to your data source and you have an option for dit, and you can see an option for filter. You can see an option for filter. You can just add any other filter. So suppose for this case, what I'm trying to do is I'm just adding the ordered filter. And for auto what I'm trying to do is I'm just adding only to include the latest data. Okay. So I'll just exclude all the data okay. Click on okay. You can also do some aggregation kind of thing if you want to roll up the data by year or month, so if you have some data prepared, so that time you can use this operation. You can also restrict it to number of rows if it is taking large volume, and you can also add incremental refresh if you want to. So I'm just save setting as of now, I don't want to do anything. So this is now the extract filter is applied. So if I take any or thing, so it will have only one year data that is the latest year 2024. Let me just do that. Perfect. So what happen is like when we use Atac filter, so it Actag will be created. So it will be a hyper extension file will be saved in your system. So as of now, I don't want to do that. I want to do all the calculation all the filters in the current dashboard, and I want to make changes like if I want to in future. So dt what we can do is we can use an option for datasource filter. So this is the filter option available. So if I add the data from here, so you can see only one thing is available here, I can only filter the data, but I cannot do aggregation or roll up the data. I cannot do additional operation here, okay? So that is the thing in datasource filter. Okay, so now the same thing has happened. So these two filters are the filters which are at data source level. So now we'll move on to another filters that is context dimension Masa filter. Okay. So now let me just take an example. So for example, like you are seeing the sales number, okay. And you are seeing the sales number by state. Okay, and by region, for example. Okay. And if I arrange in descending order. Okay. The thing is you can either give filter in the filter shelf, just drag it to the filter shelf. Okay, as if now I'm just clicking Apply all, but you can also give some kind of condition or top condition or any wildcard entry if you want to give. Click on Okay and same for region. Okay. And now what I want to do is I want to show the filters on the right hand side. Now the thing is you can customize as well. You can just click on this drop down. I want to see a multiple value dropdown. I want to customize it and show the apply button. And same I want to do it for this one. Okay. So I'll just do it first oh. Okay. So now you can see if I select central region, it will be there right. If I select South region, it'll be there, right. So everything is there right. So now the thing is what I want is I want to fetch, for example, top ten stayed by sales. Okay. But before deep diving into it, what I want to do is I want to also introduce you to the Masa filter. So if I put the measure in the filter shell so this is known as Magic filter. The orientation will be different now as of now, you can see when we're putting the dimension filter was giving us some option from the drop down. Now it is giving us the ranges because it is a numeric filte so you can either give range of value at least at more special. So as of now, I will just give range of values. So if I show the filter, so you can see if we show slider icon, so I can slide sales between these many ranges, or I can also manually enter there. Okay, so that all thing you can do. So this is how dimensional Masa filter works. So now comes what happen when we use two dimension filter. Okay. So whenever you use two dimension filters, what happens is it takes the clause. And clause means both the conditions should be true, then only it will evaluate. Okay. So the thing is, for example, I want to show for the top ten states sales. What I can do is I can just click on this drop down, edit filter and go to top condition. By field, I can just give top ten by sales. I can also parameterize if I w apply. You can see now to showing for top ten state by sales, right. But if I filter it by region, for example, Okay. So as if no it is not dt. But if I ask you if I want to do for both the things like top ten state, and top ten region. So your answer will be, you can also apply the same filter here, right? If I go in the addit filter and top and top ten by says if I want to apply region also. Okay. So now if I give the region filter, then also the thing is different tit. So what is happening is, so when we use more than one dimension filter in tableau, so what happen is take clause. So clause means like to take the common values between inner gen, you can say common values which are available in both the state and the region. Okay. The thing is, what we have to do here is instead of seeing from the entire dataset, what I want to do is I want to create a temporary table kind of thing or a materialized view based on the region because if you see the hierarchy of the location wise, what will happen is first comes the region. Then inside this region, these many states apendte. In each region, these states lies in region, the states. So that's why the hierarchy arteries, like the region is the topmost priority. So what I can do is I can add the region filter to context. So now what what happened is, so it has created kind of temporary table or a materialized view, you can say. So it is not neglecting the and clause. And what it is saying is it is seeing from the state entire region thing. So what it is doing is first it is putting the filter in the central region and he seeing what are the states available in the central region. And then from that states, it is highlighting the top ten states, and same for the other case scenario. So now if I do for each region, or the west region. You can see now it is fetching correctly. It is showing the top ten sales by state as well as region. This is one of the trickiest thing that you have to understand because in some scenario like when you're working on a real time industry, you may have scenario where you use some kind of fixed LOD or some kind of or some kind of scenario there you have to show both the things in this example, top ten thing. You should know how you should approach this problem. I hope you're clear with it. Now the thing is, we have seen this all three filter and now comes the last is the table calculation filter. Okay, so table calculation filter is simple only. So the thing is, suppose if you have any table calculation. So for example, you haven't order date. Okay. And if I do it for the month level, and suppose if I want to show sales number. Okay. And I've created a Quick table calculation percentage of total. Okay. And if I get this filter, so this is a table calcon filter. Nothing fancy here. So this is just a simple filter like the measure filter which you have seen. Okay. Okay, so now we have seen the Tableau order of operation and we've seen all kind of filter. So there are some more filters that are not available in the Tableau order operation. That is, like, I can just show you two more filters. So one is like cascading filter. Cascading filter mean like suppose you have category and you have subcategory and you are showing the sales number, okay? And you give the filter for both the thing, category and subcategory. Okay. So now what happens is category comes at top architect. After category, the subcategory will come right. So if I change it to multiple value drop down and multiple value drop down. So if I give the customize a show apply button and customize that show upplybton, okay. So the thing is suppose if I change furniture. Okay. Then you know inside furniture like these four subcategories is there. But in the filter, it will show me all the things. Okay? So what I want is I want this filter to change according to this, okay? So what I can do is I can just click on this drop down. I can click on only relevant values. Okay. Now if I change it to supposed technology, so you can see it will only show the options that are available inside technology. So the other filter is getting filtered according to the relevant value that is there in the data set. Okay? So how cool is that right? And we also have filter actions in taboo. So what does filter action mean? Suppose I have a dashboard, I'm just going to a dashboard. And if I add like certain graph profit dash date criminative, um or just I'm adding it as if now just randomly. Okay. So now the thing is, like, for example, I just remove this for this instant. Okay. Okay, so for example, if you're using this filter icon, so if you click on that and if you click on California, then you can see this is changing dynamically on the inside. So if I'm clicking that, so you can see all my calibration is changing. So if I go to this sheet, so you can see an action button applied here. So this is known as filter action in tabu. So this is also a kind of filter, you can see, but this is more like a action button. So this is also like you should be aware of. So I hope we have covered a lot in this video, and we have seen like different kinds of filters in tabu. So now see you in the next one. 19. Advanced Session: Map Analysis in Tableau: In this particular video, we'll be learning about how to customize map in taboo. So we'll be building a map visualizations in which we'll be showing our profit ratio and giving the user the flexibility to select the profit ratio for the selected states, for the top 20 states, and for the different parts of the region, they want to see. So there's a lot to untag in this particular video. So see you in the video. So what we're going to do is, uh, so let's get started. So let us just connect to a superstore data set first. So just go to your table repository where you can find your Superstore dataset and connect to it. So once that is connected, so what we're going to do is we are going to deal with the order sheet in this particular example. So just drag the order sheet to the right hand side. Perfect. So now let us move on to sheet one. So what we're going to do is we are going to create a Mapson and we want the user flexibility. To select from different options, right? So we will be going to create a parameter first. So before creating parameter, what I'm going to do is I'm just going to double click on the state one, so perfect and select the M type two map. And in the right hand side, you can see 59 unknowns. So just click on that and click on Added location. So what is happening is, as of now, Tb taking the country as region. But we are dealing with a particular dataset that contains the data of US. So in order to work, just click on this dropdown and click on From field, so it will take from the dataset. So in the dataset, we have United States and Canada. So click on. Okay. Perfect. So our map visualization is a little bit ratit, but we will be giving a modification to it. So just create a parameter first. And what we're going to do is we are going to create a parameter that we want the end user to select an option, right? So laptop group. Okay. And we're going to give it as a string, and we're going to give it as a list. So what we want user flexibility is we want the user to see the map visualizations by top ten states by sales, right? So just give it as top ten states by sales. Then we want it to show by central vision. A little central region. North region, West region. And we want user to select custom select custom states. We want the use of flexibilitive selector custom states. So these are things we want to give. So just click on Okay. And let me just cross verify the region leases so that we are correct, central east, south and west central east south west. So central North region is not there, so we'll just give it as East. What? Eastern region. We can give it. We can just give our name as Southern region, Eastern region. Western region. Central region. Okay. And now it's perfect. So click on okay. So now this parameter to work, we need to wire it up, right? So how to do that. So what we're going to do is we are going to create one calculation to wire it up. But before doing that, we need to create some more custom sets in order to this calculation to work. So how to do that. So in the state one, what we can do is we can create a set and we can give condition. And what we want to show is we want to show top ten states by sings. Okay, we want to give it by field and we want top 20, and we want it to be filter by sales and click on Okay. Perfect. So now, in order to see that, just drag the state to the Row shelf and just drag the top 20 states by sale, and just drag the sags to the tax shelf. And what we can do is we can just sort the state by S number. So by field, descending order SAS. So you can see for the top 20, it is inside the set and for the other one, it is outside the set. So this our top 20 set is working fine. So now what we're going to do is now we are going to create one more set, and that will be the selected state. That is the custom one sector states, and we'll be not giving anything as of now, Helicon okay. And I I try the selected state to the right handside, so as of now, you can see all or outside the set, right? So if I show this set the right hand side, and if I give it a multiple valued drawdown, and suppose if I select California to it, so you can see in the first one it is showing now in because the user has selected that. So our selected state set is also working fine. So now what we want to do is we want to give it as a calculation, right? Like for selecting all this group, we have to wire it up. So how to do that, show the parameter. So we have to give one, two, three, four, five, six, six calculation. So how to do that, just create one calculated film and just name it as filtered states. And what we are going to use is we are going to use a casettment. So just case parameter. So when the user select top 20 states by sales. Just beware like this. The wording should be similar to the wording you have given the parameter. Otherwise, it will throw us an error. So if this is the case, then what we want is we want to show our top 20 states by sales. Okay. And when the user select the second option that is central region. And then what we want to give is, then we want to check if our region equal to central then two as calls and we can just copy this calculation p condition, and in our side it is washed then to two. Otherwise, a large condition, like when it is like the selected custom states. Upstairs. Then we want our selected state set cult and we want to. So our calculation is valid. So I hope you PA bid. So just click on Apply, click on Okay, and just check if this is working. So just tag the filtered state to the right hand side. So as of now, I get a top 20 states, so that's why is showing true for all the top 20 and for the other one it is shown as false. So if I select central region, so it is taking central region I suppose, for Southern, it is showing different values, so it is correct and for selected custom states. So as if now it is showing all the values as false, if you see, right? Suppose if I select California, so it should show true. If it is showing true, then our calculation is working fine, perfect. So our calculation is working fine. So we have created our parameter, and we have also wird it up. So now what we need to do is now we are just going back to our sheet, and for just we are going to show our parameter here. So as of now, it is not working because we have not wired it up in this particular examples. We are not showing anything into detailed shelf field. So what we're going to show here is we are going to show our profit ratio, right. So just create our calculation. That is profit ratio. And it'll be like sum of profit. A advice, sum of? Si. Perfect. Click on apply, click on Okay. And what we're going to do is we are going to give some condition here, for the profit ratio. So this is one of those channels from Waku Wednesday. So you can see, like, we have to divide up profit ratio in four category. Like, for less than 0%, profit ratio, it is unprofitable and below 25%, it is highly unprofitable and above zero and 0-25, it is profitable and above or equal to 25, it is highly profitable. So what I've done is I just written down one calculation for the profitability. What I'm doing here is if it is electing our filter state, then I've given all the condition if our profit ratio is less than equal to minus zerot five, 25% is minus zer 0.25, then it is highly unprofitable and all the conditions are given. And if it doesn't match all these condition, then we want it to be not included. So just click on Apply, click on Okay, and just drag this profitability to your color shelf. Perfect. So now what I'm going to do is, I'm just going to show my color legend. I'm going to show my color legend. So in the Analysis tab, you can go to legends and you can just go to color legend. So now what I'm going to do is I'm just going to give the custom colors to it, and we'll be doing as per challenge. So let me just go to the tbluPublic profile and just track it. And strike it to the left hand side. Strike the drag it to the left hand side. So what I'm going to do is, I'm just going to pick the color. So this is one of the trick, you can say, to pick the color from any other particular website or any particular sheet. So how to do that, select your the mark shelf. So just select your color shelf which you want to change. So I just selected the higher profitable category and just click on pick screen, and we can just pick screen from this one. Highly profitable. So for profitable, it is not selected right, I think. For profitable, I'll select again. So for profitable, I want this color to be shown. Click on Okay. Perfect. Now, click on Okay, and just it is the size clean. Perfect. So now our profit ratio is this strain correct. So now what I want to check is like if our filters outing fine. So this is for top 20 states. I want to see for the central region, this ran for central region. If I want to see for southern region, perfect. Eastern region. Western region. And for selected custom things, I have to show the selected states set on the right hand side and just give it a multiple value drop down. So if I select, suppose select all the one, perfect shines customs one, so it is shrine. So all the calculations are working fine, so it is perfect. So let's go to drop states. So now what you want to give is now in the particular challenge you see. So what they have done is like they have shown the profita for the selected states and profit istio for the non selected states. So we're going to show that. Okay. So what is? So first, we need to create a calculation. So what is the calculation we need to do is first we create a custom for filtered data, like the users the user pattern, like how they're filtering. So what I'm doing going to do here is I'm going to write a fixed laborail expression. And in the fixed level of detail, what I'm going to do is I'm just going to give the filtered states. And what I'm going to give is, I'm just going to give a sum of profit. Ratio. Okay. Okay, it will be noto sum. It's already aggregated. So I'll just giving the profit ratio as it is already aggregated. Perfect. Click on Apply. Click on. Okay. So now for selected and non selected, what we are going to do is so let me just just so I've just written the calculation for filtered state. So let me just write profit itieF selected states. And what we can see here is what I've done here is or just has the pith. So what I do, let me just give you a brief overview what I've done here is. So if the user select from the filtered states, if the user select from this particular options, then what I want is, I want to give it the calculation that we have built for the profit ratio. Like for the selected group, fixed selected group, it is creating the profit ratio, right? So, click on apply, click on Okay. And what we're going to do is we're just going to duplicate the same calculation and give on add it. And this would be like profit ratio for not selected states. So what I'm going to do is just in the conditions filter states, then I want the PR one. So click on apply, click on Okay. And what I'm going to do is I'm just going to Control click both the things and drag it to Detail Shelf. Perfect. So now, in order to show it on the right hand side, what we can do is we can just click on the left hand side, particular state. And what I can give is I can just right click on that and you can see the annotate option and click the mark. And what we can do is we can show move all the things. And I want to show for the selected states. I'll just show for the selected states, and I will just do a little bit formatting. So just select this one Command X, and Command V. And just select all center. And for this, I want to give it the 18 size. And for this, I want to give the 16 size. Okay. And this I want to get the bolt 18 and 16. Okay. And what I can give here is just select for selected and no selected and just change the fault properties of number format to be percentage, zero and decibl and one more thing, what we can do is we can just select both the thing and we can just change the default aggregation to average because we are using a calculation, the average one, right. So just drag it to the left hand side. And what we can do is we can just click on format and you can see on the left hand side, we have some modification we can do, so we can just give you the very downed corners. And for the line that it is showing in the map visualization, we don't want this line, just click on none, and we can just add just the texts. So just click on the dit option. Yeah, you can just light it as proffered pastry fault, selected stairs. Click on a flag, click on okay. Puff right. It's okay, fine. Now, we want to show for the non selected states on the right hand side. So what we can do is just select the extreme one, anyone you can select. So just click on Mark Label and sorry notate, click on Mark and all the things like all the fonts should be consistent. So I'm just making this as consistent. So 18 and 16 and select and center line. Click on apply, click on. Perfect. Just try it a little bit. Perfect. And what we can do is we can just edit this. Sorry, you can just right click on this and just click on format. And same thing, we can give you a very rounded bar, and we can give the selected stick or as none Perfect. So now it is perfect, right? So just I can a little bit tweak a little bit. I can just I can just check like body is looking perfect. We can make the alignment change. So now, for me, it is perfect, but you can do much more adjustment. So perfect it is. Now it is looking perfect. So now a dashboard ones. So just go to Dashboard and do a fixed size, and we can just give this as 1,200 by 800 for this portal example. Or what we can do is we can just do it as 1,000. Thousand. And you can also give it 100,900. Okay. Perfect. So now, what we're going to do is we are just going to drag our vertical container first, go to layout, give the inner puddings 20 and go to dashboard, and just like the blanks. So once I'm dragging blanks, so you can see the lines are there. So that shows like we've given the inner ping 20, that's where the blank is coming in between. So once we have done that. So what I want is I want my vertical container to be here, and I'll just drag my sheet one. It just record this. And what I can do is I can just click on and site Map Options, and I can just disable all the things. Perfect. And just remove the title for that. And this is what I can do is I can just give to the floating and I can just give it on the left hand side. And we can also remove the unnecessary thing. We can also go to map and you can just go to map options. We can just go to Map and we can go to background layers and background layer, we can just wash out all the irrelevant layers and icon of fly, now drag the profitability to the left hand side. Perfect. Now what I want is first I will just give it both as fluting, this also as fluting teres here. And this also as a floating one. And just as here and just remove this container. I just left hand side and left hand side. So now what I want to do is, if I select a selected custom sheets, then only this selected states option should come. Otherwise, it should not come. So here we we'll be using our new feature in taboo data is introduced. That is dynamic zone visibility. So how to do that, just create one calculated field and just select a group. Like if a selector group, like if a parameter is equal to selected custom states. So just write it here. Selected custom states selected states filter. So what it is doing is it is giving us a boolean value, if it is true or false, right, so click on apply, click on okay. So we can use our dynamic zone visibility using our true and false conditions, right. So select dis filter, go to layout, control visibility, selected states filter, perfect. So now if I select central lesion, it will show for central southern lesion, perfect. So now, let me just give it a slide. So if I select for central region, it is fran for central. I'm selecting for southern region, it is fra for Southern. If I select top 20 states, it is framed for top 20 states, if I select selected custom states, then this filter is coming. And if I select any particular, like, Like I select, suppose, from this to this I select. Perfect. So now all the filters are working fine, and we have learned how to customize map and we can just give the profit ratio in the label. So now what we can do is we can just add the dashboard title. And the dashboard title, but we can give this we can just give this same title You can just copy this from this and just paste it here. Deleted. Click on apply, and we can just increase the size it a bit the 18. And this has 11 apply. Okay. Perfect. You can just catch this from Selectors I can just give it filled. So let me just click a floating one. So I will just hit a horizontal container one that is floating, and I will just adjust this size. And if I drag this floating to so if I select this floating container, shift drag into floating contina so it so it will be fixed. Perfect. And the same thing we can do it for this particular filter. So what I can do is I can just drag a horizontal container first. And I can just track this filter. Decrease the size that at this perfect. And now it's like from custom states. So we can also fix that also. So just give it to the horizontal antena first. That is floating one. And just shift control drag. Perfect. So now it is fixed. So now, nothing will change. Let just present the screen and show you the recap what we've done so far. So what we have done is, like, we have given the user the flexibility to select a profit ratio for, like, different options, like, like from particular region, he can do that. If you want to see the top 20, he can do that. And if you want to see from the custom list that we have in our particular data set, he can do that, right? So suppose give us like from Illinois to MinisipA so it is showing that, right? So this shows the true capability of tabu. And we've also learned, like, how we can use the notate tool to, like, show the KBI cards like in the same abatization. So that shows, like how cool tableau is. 20. Understanding Patient Volume -KPI: Now since we have understood about the data modeling thing, and we've also learned how we can use calculations like calculated fees, table calculations, and level of data expressions and which kind of chart we should use in which kind of scenario wt. So now moving forward to this case study. The first thing which I wanted to look into this data set is the patient volume, how the patient volume is increasing year by year or month by month. Okay. So this is the first KPI, how to deal with it is what I can do is I can just take my patient ID from the patient table and I can just do a count distinct. And then what I can do is I can just add the start date. So now this is the overall trend. So you can see the overall trend is decreasing, right? But this is for the overall level. But what I want is if I go to New Sheet and if I add the encounter class, you might see there are different sections like there's emergency section, urgent care section, inpatient and outpatient. So I'm interested in the inpatient, the volume of patient data coming to the hospital. Okay. So I will just drag this encounter class to the filter shelf and change the filter to inpatient. So for this also, it is decreasing. So now you can see this tree is the latest year and the previous series, 35, okay. So what I want is I want to find out the year over year change. So for that, what I have to do is I have to find out the patient volume for the current year and the prior year, right. So I just create one calculated field, so I can current here. So for current, what I can do is I can just write if condition, if and has condition. So if my year of start, is equal to the maxim. So maximum, I have to enclose in calibraces. So it will take for the entire dataset, that is table Sco Paludi. So here of start. And close. So if this is true, then what I want is I want my patient ID to be returned, right. And what I want to do is I want to do the count distinct. So I just enclose the I into count distinct and click on applaq click on Okay and drag it to the details shelf. So I'm doing eta shelf is because I want to show this as in title card. So double click on this, remove the sheet name and insert it. You can see now this option is available, right? Click on apply, click on apply, click on o. So as of now, you can see it is showing me the range because I'm showing for the date range, right? So I want to fix it. I want to calculate total. So there is an table calculation. So if I add this calculation and just write total one function. So what it does is just create a total for that entire year. So apply, so perfect. Now I can see it's string three that is the correct number. And same thing I want to do is I want to add for the prior year. So I'll just duplicate it, di duplicate, and just edit it. So now for previous I can just write maximum year minus one. So one year back, I want to and just change the name. Per year. And now I will just add one more calculation before moving forward. That is year over year change, year over year, patient volume change. So that is just simple like that is current year. Minus prier, divide by prairie. So this is how we calculate a percentage difference right. Click on appl, click on Okay, and drags the same thing to detail and just add it here down here change, and from prior, I'm just checking. Okay. So from prior and center and second we number of number of patients admitted. Okay. Apply. Okay. Perfect. So now for percentage, I want to change the formatting, so just slide click on this format and go to pain. Number format, percentage. One place asimum. Okay. Now just a little bit adjustment I'm doing doing this as bold. This percentage as bold. Okay. Click on apply, click on Okay. But what I want to do I will just do all the things bold, okay? And just change it to table semi bold. And we'll just reduce this size. We'll just remove this from bold, this and this. Okay. Icon of player. Perfect. Okay. And for the volume chain, I can change it to red color because it is declining, but this is not dynamic as of now. We can make it dynamic if needed. Okay. So this tell us how our trend is going right. Now what I want to do is I want to change the color. Before doing that, change it to tie. Change this label and color, click on color and more color, and you can write to hexagon code. So 55555, I'm using here. So apply. Perfect. Now what I want to do is I want to highlight, suppose for example, I want to highlight the minimum maximum sale with the dot there. So how to do so. I calculate field. I'm just writing minimum maximum color, and I'm doing it for patient volume, so patient volume. So what I can do is I can just cite if my count destined patient ID is equal to, I have to find it for the entire window, so I can write window function, Window Max. Of this. If the window maxim for the entire window is there, then I want green. As check if count distance of patient ID is equal to Window the minimum one, then I wanted to highlight with the red color. Click on apply, click on. Now in order to do so, what we can do is there are two ways. One way is I convert this to a bar graph, and I just drag this to the color shelf just change this color thing. For null I'm just giving the color as high ste 55555. For green to green and to red. Apply. Okay. And uncheck the header and also drag this Control click, drag it to labels, and just make some adjustment here. Click on this labels one, match color, and alignment to middle one. So this is one of the way I can do. Another way is I will just duplicate this and I will just write here as line. I will just convert it into line. Okay. Now what I want to do is I want to give the same code. I will just move this from color code. Okay. Now what I want is I want the maximum minimum to it by circle. Okay. So in order to do that, what I have to do is I have to create one more access. Control click here to create one more access. Then I can just give in my second one, I can just remove all the details and I can just put my color code in the color shelf, and change it to circle. Perfect. And reduce the size a little bit. And for the black one, I will just do it a transparent color. Okay. Apply. Perfect. Okay. So now what I will do is, I'll just do the dual axis thing. Perfect. Right click and synchronize axis. Whenever you are making a dual chart you have to synchronize the axis. So all the scale is same. Remove the header. It's not perfect. Remove the labels. I don't want to show the labels. Okay. Only I want to show Minear maxim. Okay. Uh Okay. 48, and this is three, so I can just highlight it a little bit. Okay. And what I can do is I can just click right click Format and do the formatting as none. Okay, perfect. So for now, I have to give a black color, 55555. Apply. Okay. 555555. Okay. Apply. Okay. I have to give the same color because I'm using the same calculation here. How we can create a KPHart now you can see credit two kind of KH art. One is the bar visualization, one is the line visualization. So I will see which one I would like better and we'll use in my final output in the dashboard. But as in now I will keep both of them intact, okay. Let us just move forward in the next video. We'll see how to create a patient admits there. But now I want to calculate how many patients are getting readmitted. So that means like the patients are getting readmitted, so the patient are not recovering fully, right? So that will be a major drawback to the hospital, and hospitals should look into it. Okay. So I will just save this file as of now, and we can also save this workbook and we'll see you in the next video. 21. Understanding Readmitted %-KPI: We have seen how to develop KPA kind of dashboard, and we have seen one of the KPI that is the patient volume. So now what I'm interested is I'm interested interested in knowing what is the readmitted rate and how many patients are getting discharged right. So we have to build some kind of calculations. So the first thing which we can do is whenever we are starting as an analyst, to build some logic or build some kind of calculation, we have to go in the granule level, what the data is about. So what I will do is I just drag the patient ID, and I just drag the start and stop time. So when the patient got admitted and not admitted, so I'll just change to exact date. And this also to exact date, and then just turn these two field as discrete. Because I just want to show the header. Okay. And I can just switch, start and stop. So now what I want is I only want for the patient that is like inpatient, so I can just give the encounter class filter, and I can just lag the inpatient. Apply. Okay. So these are the patient you can see, for this patient like start time is 21 of apparel and stop is 22 apparel. For this patient, 24, 25 appril and then again, the patient got readmitted 17th of December. Okay. So now what we can do is we can see the first time the patient has admitted. So first time date for patient. Okay. So what I can do is I can I can use fixed the ID level and I can just do a count. Oh, sorry, minimum of the start filter. So it will give me the first start date. But the trick is like I have to also give the filter. Like, I have to mention my encounter classes in patient because it might be different for different patient right. If I don't use encounter class filter, then it will give me the minimum date for this patient. There might be case like this patient has been targeted to some ambulance service or something like that, so I don't want to do that. So and close the Kalib Muscatio. Okay. So now you can see our calculation is valid. So click on Apply, click on Okay. Then you can just drag this to right hand side. So once you do that, I have to do as a discrete field, and I have to do exact date and discrete field. Okay, so no perfect. Now you can see for this patient 21 L, this patient 24 L, this patient 12th of February. So our calculation is correct. Okay. So now what we can do is we can calculate memo field, that is the date difference, that is days of day. And what we can do is we can just see the date difference between the first time the person has done and the stop the last time. Okay, so if I calculate that and just get two labels shelf. Okay. So now it is showing me the date difference between the stop date and the starting the first time the patient has visited. So what I will do is I will take backup of the date difference is like less than 30 days, if the patient is visiting again. So that means like that patient is not readmitted. But if it is more than 30 days, then it means like it has readmitted. Like you can see for this patient, it is coming after 238 days. So this is the uh of readmission after 2232. Okay. So what we have to do is we have to create a flag, right? So how to create flag is, we can just create a more calculated field and we can just rename this as readmitted flag. Okay. And now what we can do is just think about it. So what we can do is we can just take this column, so I can just take if my encounter class is equal to inpatient, right. Then again, if condition we can give, if my days to have calculated is less than equal to 30, then I want to give that flag as a zero s one. Okay, click on Apply and there's some error. So let me just check this. Okay, we have two if conditions, so we have to write two. Okay. And again, perfect, apply, and just drag this readmitted flag to the right hand side. You can see for this case, the first day difference is zero, and for other, it is one tight. So our readmitted flag is calculating correct. So you can see for this patient, like the day difference is nine days and after 16 days, he is revisiting. So this is also not a case of readmission, so I've given the flag a zero. Okay. Our calculation is perfectly working fine. Okay. So now what we can do is just now it's a simple factor, so I can just write readmit it readmitted. Patients. Okay. And what I can do is I can just keep count distinct. So if my readmission flag equal to one, then what I want to do is I want to count a patient ID. And Okay. And click on apply. Click on Okay. So this is my readmisation. So let me just create this is just logic building I can write. So I hope you were able to understand. So if this is the first time you face some challenges, so I'll just advise you to go through it once again slowly, by your own per so you'll be able to understand it quick, faster. Okay. But there might be some other ways also to calculate the same KPI. So this is one of the way which I'm going with the challenge. Okay, so what I will do is now, I will just check the start here and I will just add the KPI, you have calculated readmitted patient. Okay. And now what I will do is I will just calculate two more KPIs, the admitted patients. So for admitted patients, it will be like a count distinct of patient ID, right? And the condition will be like if the encounter class is inpatient, then I want to count distinct. So and click on apply, click on Okay. Double click. You can see admitted patients 20 and readmit seven, then 351247, 25, 28, 24, 33. So the gap is decreasing right. So basically the percentage of readmission is more. So in order to justify that, what we have to do is we have to also check the discharge, like how many patients are getting discharge right. So I can just calculate one more KPI, that is discharge. So what I will do is I just do the same thing, count distinct of patient ID. I encounter class equal to inpatient. Right. And my stop time is something, is not null, right? So if my stop time is given. So that means like the patient has been a discharge, right. So stop then and right. So this is how we are creating the calculation discharge, so double click on it. So you can see this is the discharge. Okay. So now what I can do is I can just calculate the readmitted percentage, okay. So re admit it. Percentage. So what I can do is I can just take the readmitted patient, divide by the number of discharge patient have been discharged. Okay, supply it, okay, and double click on it, and click on format, change it to percentage. So you can see the discharge like readmitted patient have been increased to 100%. So that is alarming stage, right? So I can just write a this is logic Building two. And now what I will do is I will just do my readmitted percentage KPI. Okay. So what I will do is I will just add the readmitted filtercN calculation, readmitted patient, and I will just do it by start, right. So you can see this is the trend it is going. So what I have to do is I have to do the percentage thing, right? This is the wrong KH I put. So readmitted percentage, I have to track right, so I have to see the percentage. So now the thing is I will just change this to same color that we're using to be consistent 555555. Okay. Perfect. Change it to entire view, remove this. Okay. And or rotate this label. Okay. The same thing we have to do for current year and prior year, last two year percentage difference will just calculate. So what I will do is I will just show you one more method like we can do. So we might have not here one more function. So what I will do as just introduce to one more function here. So one function is like the last function. So if I just create one function, last, okay, I just kip last. So this is a table calculation. So if I give last function, and just give some space. Okay. And click on apply, click on Okay. And if I just drag this to the right hand side, so you can see it is just calculating the numbers. Okay. According to the last, starting from zero. What I can do is I can give condition, like this. So for example, readmit it readmit it. Readmitted percentage, current year. So what I can do is I can just give if my last function is equal to zero, then I want to give my readmitted percentage. That will give me for the last year, right. What I can do is I can just write it simple here, last function here. Perfect. So now it's working fine. So apply it and click on Okay. And I will just duplicate this and just do it add it. And if I do for prior year, I can just give last equal to one. That will be one back Sp right, one. So last is 100% and then it's 74 percentage. So just verify from the chart. So I'll just drag this two into detail shelf. Going forward, same thing. Current value, prior value, apply. So you can see 100%, and this is 7,470.29 percentage, right? So this is correct. This is the one. So for 21, it was not popping up, but this is the value here. Okay. So we are correct in my calculation. So now what I can do is I can just calculate them manually as if now manually I'm calculating 100 -74.2 9/74 0.29. Okay. So it is 34 percentage ATAs increase. Okay. So what I can do is I can just cite plus 34 percentage from prior year. Or you can also light some calculation here again. The same we have done in the first example. So it will practice for you, so you can just take it as assignment. And if you face any problem, you can just write in the command box. I'll be happy to interact with you and we'll help you in the solution. Readmitted patients. Okay, and just do it bold and we'll just do tabssign board, and we'll just change this to not bold and this to not bold. Okay, and click on Apply, click on. Okay. Perfect. In this I can just do a red color because readmission rate should be declining. If it is increasing, then also it is alarming sindte. So that's why I'm just giving that and just write it here, current here. Okay. Perfect. So it has increased to 34 percentage, right? That is the alarming stage. So uncheck this header and format and grade line, do it none. The same thing which we did earlier. None. Okay, so this is the second KPI which we have built, so I'm happy with this as of now. So let us just move into the next video and we'll see like there's assignment for you like to calculate the average time stay. Then we'll meet in the assignment video. So see you in the next button. 22. Understanding Avg Stay -KPI Assignment: Now the thing is you have to calculate the average time to stay. You have the start date and the top date, right. So you can easily calvate the average time the patient is staying and you have to plot it over ear panel right. So this is a quick assignment, go through it once and we'll see you in the next one. 23. Solving Avg Stay -KPI: Like you were able to solve this business problem. So the 30 KP H I told you to walk upon is the average time to stay. Okay. So what I've done here is, so I'll just show you the calculations. The thing is very simple. What you have to do is you have to just calculate day difference between the start and the stop time. You can also show the day level, but hour level was more friendly to me because for day level, it was less than one days. Average day was there for most of the users. So that's why I chose to take an hour. I'm checking the hour. So this is like one point this is the average hour. So once I've calculated this, so I'm just dragging it to the row shelf and taking the average out of it. And then the same thing I have done here for current year, you can see if year is maxim year, then they stay. Only thing is instead of some just adding average and the same thing for prior year I've done, and the same year over year change, right? Then the thing was, you can see, I just modified this average number of hours stayed. You can see there's a decline in the average number of hours stay because the patients are less, so the hours will be also less right. But you can see in 2014, the hour was more. There might be see the frequency might be more or there might be reason some patients were not able to treat properly and they are taking time to recover or something like that. So we have to investigate into the past data if you want to know that. So that all you can do in your journey. So I'm satisfied with the three KPIs like Dat we have developed. So now what we'll do is we'll move forward to see what all other visuals or other KPIs or we can track, and we can show to the stakeholder and then we'll formulate a main dashboard, right after, we'll complete all the things. So see you in the next one. 24. Building Insightful Tables in Tableau: So till now, we have seen the patient related KPIs, patient volume or readmitted patients and the average time the patient is staying right. So now we should also move the focus toward the stakeholders will be interested in knowing what the payers associated with the account, and what are the payers, how many money is being covered by the payer. So let me just move on to my data dictionary. So you can see there are three cost measures. So you can see base encounter cost, total claim cost. So total claim cost, the total cost of the encounter, including all the line item. The base encounter cost is the base cost of the encounter not including any item related to medication, immunization, procedures or annual services. So basically, this is the total cost that will happen to the patient if you add this up, and this is the coverage, the coverage that has been paid by the peer, right? So the pay and we have in the peer table, right? So the thing we can do is we can just calculate the out of pocket things out of pocket means, for example, this much amount has been covered by peer and this much amount you have to pay. Okay, so this is the out of pocket. You are paying some amount from your pocket right this out of pocket that we are calcrating what we can do is we can just calculate out of pocket percentage, like how many percentage we are paying from a pocket and how many percentage has been covered by the claim. Okay. So that can be the KPI that the stakeholder will be interested in, and they can see the inside right. So now let us just move and we'll just walk up on grating one table format. Okay. Like this. So now the thing is, we'll just go from scratch. So let me just go back to my just go back to my tableau interface. So what you can do is you can just write insurance level detail. Okay. So now what we can do is there's an option in Tableau that is launched in 2024 version. So that is like a tableau extension. So we can use that extension in building that. But before that, we'll just try to build a calculation first. Thing is, I want to add the pay information. So the pair will be like, these are the different peers from the payer table, I will just because it will be the name there. So this is the name. So you can see Athena anthem, Cigna Health, Dual medi claim. Sorry, Medicare, no Insurance or United Health right? So what I want to do is I want to calculate the out of pocket thing, okay. So how I can create this so I can decide total cost, total cost. For patient. Okay. So total cost for patients, we can just add these two up. That is my basin counter cost. I can just sum this up, sum of basin counter cost. And plus the total claim cost, right. So this will add up my total cost of the patient. That is being. Okay. I can just double click on this. Perfect. So now the thing is, like I have the payer coverage, this much will be covered by the peer, Okay? And this is the total cost. Okay. Now what I can do I can just calculate out of pocket. Okay, out of pocket, I have to pay money. So the total cost that has been there. And if I minus it with the pair coverage, so it'll give me out of pocket right. So if I click apply, okay, and double click on it. So you can see this amount, I have to pay. Okay. But this is the field. So what we can do is we can just convert it into the percentage. So it will be much more easier for us to understand, right? So what we can do is create one calculated field and out of pocket that we have created, and I can just divide it by the total cost, right? That has been happening. So I can just write out of pocket percentage. And apply and okay and double click on it. And I can just change this to format and change it to percentage, right? So this is the percentage that we are getting. Okay. So this is the thing that appear to pay out of pocket, okay? So it is very big amount, so that is a higher risk that you are showing, okay. So now the thing is, I can just calculate one more calculation in percentage. So what it does, how much Killen is, like, being paid by the insurance partner. Okay. By insurance partner, you just said. So what I can do I can just apply. Okay, and I want to spread 100 from it. And now if I drag this, it given 99 so that something is fishy. So if I do one minus this, then it is converted into zero thing. And now if I change it to percentage, so if I drag this a little bit down, and if I change it to percentage now Perfect. Now it is correct field, right. So I have to just subtract one from it because it is already a fraction part. So we have connected as a format as percentage, but in the majority is towards the fraction only that's I have to subtract with one not 100. Okay. So click on. Okay. So this is the KDI that will be interested, right. So now what we can do is we can just create some kind of modernized table so that it can be good for audience. Okay. So how to do so. So I will just create one cald field. Oh, sorry, new seld I will just write insurance related insights. Okay. And now we'll be using the new feature, that is a taboo table extension. That is a new feature that taboo has launched in 2024 version. So if you're enrolled in this course, so you are one step ahead again with the user who are older to tabu, they might be not aware of the feature or they might have not worked tail yet. Okay. So how to use that. So just click on this drop down. You'll see option for Add extension. Click on Add exxtension. So just wait some second. So you can see Built by tabu. So you can see taboo table. So just open it. So before we have to do so many calculations to build a table like this in taboo, but now it is so handy. So just click on okay. Perfect. So now the table is there as of now, nothing is there. So the thing is whatever dimension you have and the measure you have, you have to just drag into detail to show in the canvas. Okay. So what I want to show is I want to show the PNM, right? So I just type per, we just go name and drag it to details. Okay, now you can see the table is circulating tight, and we can also want to add a calculation to filter by calculation. And the first thing is, I want to see how many patients are there inside this peer, okay. So whatever we do I just add ID and just drag the patient ID to details shelf. And instead of the dimension, I was just convert into measure, count distinct. Okay. So this is the number of patients that have been involved by these peers. Okay. Now the KPS that we have calculated calculation, claim percentage by insurance company. Okay. Then we have our out of pocket percentages, right? So these two are things, right. So now what we can do is you can see now the option for search is this. So suppose if I want to have no insurance. So you can see this will be highlighted. Before that, it was not available in time. Okay. And some more features of there I will be deep diving into now. We can manually change the column name, so I can just write a number of patients. So I can just write hashtag patients. Okay. And this is perfectly. Only thing is what I have to do is I have to just remove this aggregated thing. Okay. Or what I can do is I can remove this claim percentage shots but because we already know this is the claim percentage, and this is out of pocket. I can just remove this aggregated thing. Okay. Now the thing is we can give the color coding or data bass, we can add in this table. So this is the new feature, right. So let me just tell you how to do so. So what you can do is you can just select the column, click on this drop down, click on format. It will show a pop up like this, and it will have all the formatting thing. Like in Paw, you might be familar this kind of thing was available. So now Taboo has also introduced this. So we'll just wait for a few seconds. So I can see show custom formatting formatting style, you want to give font style shading and the conditional rule, if you want to give any rule. Okay. So what I want to do is I want to show this is a data bar of the patient number, and I want to give the color code as see you know, the gray color code kind of or a little bit light gray, you can say, a little bit dark little bit more dark, Okay, this is perfect. And I want to give this as a bold. Okay. And I want to show the mark test, like the numbers, I want to show the numbers. Okay. Perfect. So I can also sort it by. If I want to sort it, I can sort it by designing order. Okay. Now the thing is, like, we have to see for the clean percentage. So now what I want is I want to show the out of pocket first okay. So out of pocket, I want to highlight the percentage is more. Okay. Then I want to highlight with a red color. Like we are spending more money from our pocket, right. So there insurance company is not that much useful. So we have to look into that, okay. So now the thing is, first of all, I will just convert these to percentages. So what I can do, I can just write percentage here. So this is the first claim percentage and out of pocket. So I'll just go by one, right click default properties, number format, percentage, and I have to do it one place decimal. Okay. And same thing for out of pocket format orfa properties, number format, and percentage and place the simal. Okay. Perfect. Okay. Now I'll just give the color code. Click on this, drop down, format. I take some time. Okay, sometimes it happens like it may happen in the background, it may show you. So you have to be aware because it's the new feature, so there are some bugs going on. So just click again and click on format. So now just wait for some seconds. So actually, it is doing all the operations in life, so that's why it's takeaking some time. But I think in the future updates like they will solidify it faster away. So now I want to give a color scale, and the color scale, it is limited. I cannot add any additional color palette. That is possible in the other thing. But as you know, it's too good. So what I can do is I can just heal it with the orange gray color palette, and I don't want to give any condition. Okay. So now you can see for the no insurance, out of pocket is 100% that is like I can assume, if you have no insurance policy, you have to pay all the money from your pocket. But the person who are taking Humana, Atna, United Healthcare, Cigna Health. So all are paying out of pocket 100% 100 percentage volume, and zero percentage is being covered by the insurance partner. So that is alarming situation. There might be some flaw, either the dataset, there might be some flaw or, like, we have to see investigate. Like this company, is not fulfilling the claim. So there might be cases like if you have some kind of dental surgery, that dental surgery is not being part of that insurance, and you were not allotted any money for the claim. So we have to see what all things are there. So this is the one of the way. I'm just telling you, like the people will be investigating and they'll be knowing what all features are there. So for Medicare, like 7%, but the percentage is low. Only for Medicare, it is like 26 percentage. The person has to pay and most of the percentage. 70 percentage of the claim has been paid by the insurance partner. So that is a good sign. Okay. The same thing we can do for this claim percentage, I can just click on format. And can just change, wait for 1 second. And same, I will give the color scale for this, and I want to give the color scale as some kind of this color. Okay. Perfect. So now you can see for Blue Cross field and Medicare, 74% 66% have been paid by the claim partners. So these two are the top two insurance company. You can say the good insurance company, which we have to alarming situation. Okay. So now what we can do is we can also add, like a more KP if you want, but as of now, I'm happy with this. So I'll just keep this. So now, let us see you in the next video. We identify, to see the seasonality of the things like how many patients like male or female, are being coming to the hospital. Like, what is the percentage, associated with it. So we'll just try to see the seasonality in data trends. Okay, so see you in the next. 25. Analysing Seasonality in the Data: So welcome back. So now what we'll try to do is we'll try to investigate more further information from a dataset that we can show to our stakeholder. So now what I'm more interested in, I wanted to know about the encounters, like how the seasonality is there in the encounters. Like seasonality means like how the month over month or year over year trend is going on. And in which season, like the patients are visiting more or the patients are visiting less. So that kind of analytics, I want to do. Okay. So I'm just writing seasonality and I want to do for encounters. Okay. So what I can do is I can just add the start date in here. Okay. And I can just convert it into month. And I wanted to show I wanted to see kind of month wise, like how the patient ID is behaving, okay. So what I can do is I can just drag the patient ID from this field and drag it to the grow shelf and convert it into count distinct. Okay. So and I can just change it to the bar visualization. Okay. And also can change the color to something like this and add it into labels, Control click, add it into labels. Okay, and just do the same thing for the encounter class in patient because we are doing mostly for that. Okay. Perfect. Okay. So now what we can do is we want to also see for the ears pattern. So I can just drag the start date to the filter shelf and ears next okay and show filter as if now. And just for 2013, 2014, I want to see okay. So what I want is I want it to be dynamic. Okay. So, the other thing also I want is I want one more thing I want is, I don't want to slack this filter. I want to add some kind of action to do that tight. Okay. So I'll just show you how to do that in Tableau. But we also want to see for the, basically the hot and the summer seasons and the winter season. I can just div the data. Okay. So for doing that, what we can do is we can just use one of the operations in table data is like reading groups. Okay. So I hope you are enjoying and going good in this course. So if so do comment out like your feedback. I'll be happy to interact with you. So now moving forward. So what I can do is I will just do the duplicate of this and just go to First ****. And what I will do is I will just create a group out of this. Okay. So how to create a group. So what I can do is I can just create a calculated field and just drag this month, Okay, and just add this as a month. Okay. Apply. Okay, and drag it to this one. So if I drag this instead of month and remove this. So you can see it is showing one, two, three, four right. But what I want is I bow the name of the month, right. So instead of date part, I can use date name function. So it will give me the month name. Apply, Okay. Perfect. Okay. So now what I can do is I have created one calculation, so I'll just create a group out of it. So I can just click on this drop down, create option. It will show an option for group set and parameter. So for group, I'll grade. So for group, what I want is, I want to club the winter seasons and the summer seasons. Okay. So what I can do is I can just convert January, select, february, Okay. Then March. Oh, sorry. January, February, March, then January, February, March, and this summer. Okay. And nomber also is a winter season. According to me. Okay. But it depends upon the person to person and the country we're living in. So just group it and I'll just give it to the winter seasons. Okay. And from apparel, my apparel, my June of I will give as a group summer season, and I will also create one more group. I will just give this July, October, September, August as the monsoon season. Okay. So we'll just see how the people are. So it may happen in mom so people may have fevers and they may have some kind of disease so you want to see the pattern, okay? So click on okay and go to a second sheet and just remove this and remove this and remove this. Okay. Now what I want to do is I want to create a doughnut chart. So this would be a good practice to know how we can create a doghut chart in Tableau. So you can just click on this drop down, change it to Pi, and then just place your calculation that you want to do in an angle. So what I want is I wonder count machine or patient ID. Okay. So what I can do is I can just for patient ID, I can just drag it to the rows first. Okay. And I can just change it to measure ground reiting and I can just drag it to angle. Okay, perfect. So now, basically what will happen is like it will divide based on the patient ID. That's why I'm given in angle. So now what I want is I want to divide on the base of color code. So the color code will be like I want to see for the pattern of gender. Okay. So if I drag gender two colors. So we can see these two other gender, male and female that are happening. Now the thing is only we have to remove this form rows. Perfect. So now I can see this is the pattern. So now what we can do is we can just drag this Control click to the labels and again, control click to the labels. Okay. So now what I can do is I can just click on this drop down and I can use my quick table calculations that we have learned. And what we can do is I can just see the percentage of total because that'll be a good parameters, right? And I can also enter gender to the labels. Okay? So you can see the female percentages more in 2015, as compared to, 2014, also females are more, 2013, female are about 20:18. So mostly the female persons are more. Okay. The only thing is, we have to add one more thing that we were seeing. So that is the seasonality thing, right? So what I want to see is I want to divide based on the season, right? So this is with the male distribution so I can just cteEncounter, by gender. Okay, now I just duplicate it. And now what I want is I want it to by the seasons. Okay, that we have calculated. So for seasons, what I've done is that we have created a calculation. So just go to your calculation here on the left hand side. So you can see the calculations that you make. I think we have made calculation one. Okay, we have not made calculation. We have created a group right, so I forward. Sorry. So you created a month group, okay. So month group, you can just drag it to the color shelf. Okay. So now you can see monsoon, summer and winter. It has been divided. Now only thing is we have to just remove this and remove this gender as well. So now it's perfect. Now just drag it to labels and change it as a percentage. Okay. So now to avoid some kind of situation, what we can do is I can just keep the two season. So I'll just remove them this monsoon season, and we'll just right click and you can just click group. Okay. And what I want to do is I want to do it in summer only. So just drag this to summer. So this is one of the ways you can do that. Now the monsoon like it is empty, so you can just dig the monsoon. Click on open this. Ungroup. Yeah, ungroup, you can do. Theletopion is not going, so you can do ungroup, so it will delete it. So clic on applau clic on Okay. Okay. So this is how your summer and winter patterns in the winter, like the person are coming more, but in summer like the quantity is more, right? So I can just see for 2016, 2015, 2014, 2022, so 2021. So you can see for all the patterns, for all the seasonality, right? So this is what the person will be looking forward. Only thing is, I have to just see some way so that I can don't use filter. I can use some kind of action button and I can just see the things, okay? So how to do so. So we'll just see in the last part of the video, like when we'll be building the dashboard. So we'll be seeing how we can filter using some kind of action item, okay. So I hope you are loving it. So see you in the next video. We'll just try to explore more capabilities we can do during this dataset, and we'll see what all we can analyze. Okay, so see 26. Analysing Mortality Rate + Using Set Features in Tableau: Back. So now let us do one more thing. So what I can do is I can just see the total cost by the payers or the total cost by what you can say is encountered typewrit. So I can just investigate that. So what is the total cost that I'm paid? So what I can do is I can just go to my encounter table, and what I can do is I can just drag the encounter class to the column shelf or the root shelf. Okay. And then what I want is I want a total cost. So basically, I can just get one care credit field. I can just write a total cost or the average cost. Average cost by patient. Okay. So what I can do is either I can take the total claim cost or I can just add these both upright. So we have total claim cost, total cost for patient, right, which we have calculated. So the thing is what we can do is we want to calculate the average thing. Okay. So what I can do is I can just do the average of mostly total claim cost. We'll cover all the thing. But you can also add the base encounter cost because it also have to be paid by the patient, right. So this will be the average one. So I can just apply it okay and drag it to the column shelf and designing order and Jin Do and drag it to the labels. Okay. What I can do I just click on the format thing and just change this to be a number format or one place mL display on hundred and this is US dataset. I want to keep the prefixes dollar, right? And I can just change the color palette to be a lighter gray. And now what I can do is we can see that mostly the cost is being paid by the patient who are incoming right. For urgent care, the average cost is 6.51 K. Then emergency is 4.7 k for outpatient ambulatory and wellness like it is lower. So outpatient like those who have completed all the procedure and there's some kind of formality left. So this might be the case because we are not fully aware of the business because this is the data set which we have taken from the stakeholder, so we can consult with them. Like, what does this outpatient mean? What does this ambulatory mean? So we have to understand it, right. Then only we can figure it out. So just hide the header, click on and go to headline and again do none. Okay, it is. So this is the final thing. I will just leave as it is. So now the thing is you can add more complexity. What I can do is I can just see analyze what is the mortality rate. Mortality rate motel litter rate of the hospital. Okay. So how you can see is you can see how many deaths are happening and what is the total patient. Okay. So for calculating the death, like you might be having some kind of feature available so you can see the patient, I have death date. Okay. So I can use that. So the side number Okay. So in order to create that, so I might be having some death date field. So you can see we have the death date field. So what I can do, I can decide is null. If my death date is null. So that means, like, the person has not died, right. So what I can do is I can decide not is null, then one s zero. Okay, so this will give me the no total number of deaths. Okay. Apply. Okay. So now what I can do is I have created a number of deaths, and what I can do is I can just create one more field that is mortality rate. So there will be like number of deaths divide by the count dition of patient, right? So I can just cite total patients. So something some of death, right. I have to give inside aggregate functions. So should work perfect. Click on apply, clic on okay. So now what you can do is you can just drag the mortality rate, and you can just see her by her pattern, how the graph is going. So mortality. So you can see the mortality rate is not that much high. Uh in this scenario, but what I can do is I can just see for the death reason, like mortality rate for the reasons. For dad I can see. I think for that cases, it makes sense, so mortality rate reasons. So you have one feel like if I go back to my literaty, so you have one see reason, why? What is the disease you have been suffering from and what is the mortality rate for that? Okay. So what I can do is I can just go to Encounter, go to reason description, drag it to here, and now I'll just add the mortality rate. Okay. And just do it like this and try to do this. So now you can see mortality is coming out to be 100% asin I'm just changing the formatting a little bit. So you can see for these diseases like suspect lung cancer, primary, small, malignant cancer pneumonia mina, there's 100% chance the person like mortality is there for this hostal. So for a this thing we have to see, like the things which are like, can be recovered fast or will have less impact should be not having that much mortality ratite in a hospital. So now the thing is what we can do is we have to see for the encounter class inpatient. So I'll just drag this and do it for inpatient, apply. And okay. So you can see for the inpatient, mostly 50% for COVID 19 also we have 47 percentage mortality rate. So for some of the visuals which are not defined in the reader set, 28 percentage. And for chronic pain, appendicets anemia, like we have zero percentage mortality rate. So what I can do is I will just see for the entire data set. Now what we can do is we can just leverage out the feature of sets in this. So that will cover into the next video. We'll just see how to see the top and the bottom ten. Now the perfect time. My need to introduce the set features. So what set feature will do is, suppose if I want to show the top and bottom top and bottom reasons for the modality rate. So I can use the set operation to do that. So what we have to do is for the reason description is that discrete field. So just click on this top down. I can create a set out of it. So once you click on the set, you can see there are three things general top and condition. So what I will do is I will create the top and set first. So I'll just click on the top by field. And instead of N, I will just create a parameter, so I can just skip the parameter name is top bottom and Reasons. Okay. So I'll give the user flexibility to choose it. So the maximum I will give it a 15. So top and bottom 15, the user can see the stakeholder, basically. So click on Okay. So you can see a wind diagonOce you create a set, the same thing I will do for another set. I will just click for the bottom one or bottom. And by field, instead of top, I will just like bottom. And from ten, I will just like the parameter that we've created and click on Okay. So when you have same dimension measure, so you can just combine the two sets in tabu. So if I click these two things and click on this drop down, you have an option for create combined set. So once you click on this, it will show me an option. So I will just give the name, top and bottom reasons. And you have an option for all members inset, share a common element, only the left element, only the right element. But as if no Avondale element, like all the top and bottom thing, okay. So I'll just do that and ca on okay, and just give it to filter chef. So now you can see, we can see the top and bottom thing. This is the top and bottom right. So only thing is I can just show my parameter. So now the thing is like I can just give it a type in. So if I write top five, I can just see top five thing. So just ignore this error that is happening. So top ten. So there's some challenges in my system, so that's what it shring but it will not string in your system, top 15, so you can see this is the top 15 thing. So this is how you can see top and bottom in SAC Operation, right? So this is a good feature in tableau that we can see. So now the thing is like we have developed the most of the KPIs and the visualization that we want to showcase. Now, the only thing is, like, how we can arrange them in a kind of dashboard, and we can tell story to the stakeholders. So that will try to cover in the next section of the course. So we'll just see in the dashboard section, how to build a dashboard, how to understand different kind of containers, and all that thing in detail. So see you in the next section. 27. Understanding Containers in Tableau: So, welcome back. So now we have built aura visualization. So now the thing is, like, how we can arrange this in dashboard. So the first topic which I wanted to discuss upon is like, how you can create a dashboard in tabu Water containers and all. So it will be like a deep dive into the basic of tabu dashboard, because these are necessary for you to understand. Like, if you'll understand this basic concept, then it'll be easy for you to create any kind of dashboard. So now the thing is you can see an icon for a dashboard icon, Windows icon, click on that. So whenever you click on the dashboard icons, you can see there are two options available here. So dashboard and layout. So layout will just show the layout of the container which we put in inside that, or if you want to put any kind of padding like spacing, so then you can do that. And in the dashboard thing, you can see an option for default mode and then a phone mode. If you're creating the dashboard for the mobile application, you have to change it to phone, otherwise, default, and you also have an option for device preview. So in the device preview, you can see like there are different options available. So you can see for desktop for tablet for phone. So this by default, which is given by Tableau, so in the size, you can see there are three sizes, fixed size, automatic and range. So mostly people in some of the company, they will do automatic size because it will automatically fix fit into the screen, they are displayed on. But in our case, I'll be using the fixed size. So fixed I'll be using kind of 800 into thousand. Okay. So what I can do is 800 into 800 kind of thing. A 900. Okay. Height. So this is the dashboard size am we'll be taking now, and I can just remove the device preview thing. Okay. So now let us just see one by one, what are different objects in tableau, Okay. Now the thing is like we have different objects like horizontal container, vertical container, text, extensions, pulse matter which is new in table 224 version, data story, image, blank, workflow, web page, we can all this kind of thing. Okay. So the two things which there is one is tied and one is floating. So floating as the name suggests like if you create a floating container, if I drag this to right inside, you can see it is easily I can move it right. Okay. And if I just cross this, if I use tiled one, so this will be fixed. Okay, so this cannot be removed. Okay. So whenever you are creating a dashboard, you should be aware, mostly in most of the cases, we use the tiled object because we don't want it to change, like if the person is seeing on any dashboard in the screen, so it should not change, right? So it should be fixed. So most people use the fixed thing. So now the thing is, we should understand like how we can use containers. Okay. So the first thing is suppose if I use vertical container. So vertical container means it is like top and bottom. So vertically, I want to align the charts. And if I bound to align horizontally, I will use horizontal container. Okay, now comes the blank part. So blank is like a space holder, you can see. I've created a vertical container. Now vertical container will store one by one, right? So I'll just add the blanks here. So one blank and drag blank two and blank three. Okay. So now what I can do is for your ease of understanding, I will just you can see this two lines. I will just just double tap on it. So this is the vertical container, which is like I'm using. So in the layout, I will just change the border to darker color. So you will understand like this is a vertical container. And in this vertical container, this is the first blank. So I'll just use this as a green color. This is the second blank that we have put. So some not borders. Borders I have to give second one, and this is the third one. Sorry, I've written. I've just like it. Okay. And this is the border. I'm just ting it to be gray color. Okay. So now the thing is, you have seen the vertical container thing, right? So now let me just introduce the horizontal continer. Suppose I want to put all the KPA charts in horizontally. Okay. So what I can do is I can just use horizontal container. So I can just dig this to right inside. So this is horizontal container, go to a layout, and as if now, we'll just add the background color. So we'll just change it to blue color. So you can understand. Then you can just reduce the size. Okay. So now you can see how we are arranging this. So suppose, for example, you have to arrange side by side. So suppose if I drag this into horizontal container and drag this and drag this. I'm just doing randomly, okay? So I can see I'm just arranging all in side by side pattern. So this is a horizontal container. So if I talk about the vertical continer for example, if I do Control, control, control that, and if I introduce a vertical container here, okay. This is a vertical continuer. So if I give the layout and background as if now as a little bit different color pink color, for example. Okay. And if I now put the sheets, so now the behavior will be different. Okay. So now you can see it is like aligning vertically right because I'm using the vertical continer. So for horizontal, suppose if you want to analyze, if you want to keep your sheets side by side, then we use horizontal container. If you want to use sheet one by one, then we'll use vertical Ctenon. Okay. Then we also have an option to add a text. So if I drag this text, here and I can just add some kind of dashboard title, and click on. Okay. Perfect. So this kind of thing you can do, you can just double click on this. Sorry, click on this line and you can just lay it around. Like you can ship this down, ship this up, so you can do that. So all that thing you can do. Then we also have an option to have a navigation buttons. So, for example, if you have two dashboard screen and we want to have a navigation button, I can just add the navigation button and you can see this is navigation buttons. So I I click on this dit button, so the ask me where I want to navigate. So suppose, for example, I want to navigate from this page to insurance related inside, just for Damm doing. Click on apply, click on okay. So if I Control click on this, Okay. Presentation mode. If I click on this, so you can see it is going to the insurance related inside page right. So Dataway you can use this kind of navigation buttons. Pulse metric, it is only available with TabluCloud if you have a tabu Cloud account, Wflow is like tabu prep, but flow, like if you want to introduce, if you've created any, that you can do, you can add the download button, if you want to have a download button, the PDF, PPT or Excel file, you can do that. So if I click on that, you can have three options PDF, image, Postb and PowerPoint. So Crosstab is just like Excel only just will act as a cross tab. Okay. So this all we can give. And we also have different options which we'll try to explore, like in further going. So I hope you are able to understand the crisp and some level of detail like we have studied here. So now what we'll do is just we will deep dive into creating a dashboard, and we'll see, like, how we want to arrange a dashboard in a way like it can convey the story to the audience, right? So, see you in the next video. 28. Designing Dashboard 01: Come back. So now what I want is I want to design my dashboard right. So I will just doing Excel, like how I want my dashboard to look like. So the first thing which I'm interested is, whenever the people are viewing a dashboard, it should have a title, right. So I'll be having some kind of title here. Then after title, what I want is I want the user to see the KPIs, like the main KPIs that the business should look into. So what I can do is I can just add the KPI charts here so I can just write KPI one, Control C, Control B, KPI two, Control C, Control B, KPI three. Okay. If you have any other more, then I can add more KPIs like if I'm having okay. So as of now, I'm just keeping this many and click on Aber. Okay. So now what I want is after the KPI things, what I want is I want to show the insurance thing like that we have credited, how the insurance partner is having that thing. So I want that kind of tabular formatite. So what I can do is I can just add table details. Okay. And then after that, what I want is I want to show the seasonality. So for seasonality, like we have credit a bar chart and we have cred, una chart, right. So what I want is I want it side by side. So side by side, that means we'll be using horizontal continua, right. So what I want to do is I want to show seasonality one Control Z, Control V. Seasonality too. Okay. And we'll see how we can keep other things, like if we have any other screen I want to keep in my dashboard so that we can think about it. So I'll just do it a color coding, so it will be looking good for you to understand how I wanted my dashboard to be arranged. Okay. And like this species Entissing it will not be blank there, so we'll be covering that. So now the thing is, let us just begin to create this kind of prototype in tableau. So I'll just move on to my tableau. So what I can do is I can just create one dashboard and I can just name this as healthcare or what I can give as hospital experience. Okay. So what I can do is the first thing I have to do is I have to change the size. So just change the size too I want to do it by 900 by 900. Okay. And then what I can do is I can just use the vertical container first, like to add the background and go to layout and give the border is black, light black only. Perfect. So now what I can do is I can just put my blank holders. So I can just put blank here and again, blank. Okay, then again, blank. Okay, and again, blank. This is just I'm doing for my reference. If you don't want to do, you can skip this part. You can just directly do that, but it'll be a good practice for you to understand it better. So that's why I'm doing that. So I'll just give the colour coding of all the blanks to be different colour. Okay, so now it's perfect. Okay. So now what I can do is I want first the title, okay? So for title, what you can do is you can just click on the top dashboard icon and dashboard. Sorry in the Rabon, you can click on Dashboard. You can see an option for show title. So it will just Certan thing. So now what you can do is you can just cite hospital Analytics, hospital performance analytics, okay? Okay. And I can just give it as a tableau, semi bold or tabu bold and just do it a size of 24 and left alone only I'm doing as of now, and perfect. Okay. So now what I want is I want to give one line also. So for doing creating one line, there's a trick in tableau. So what you can do is you can just the tal container here. And after getting tal continer, what you can do is you can go to layout, and you can just background is black, and then you can just reduce the size. So it will give me a full line. So one size, you can see a line has been here t. Not look perfect. So now what I want is after like my title, I want the KPars to be shown here. So we have the KPHRs we have created wt. So what you have to do is we have to create side by side. So we have to use horizontal container, right. So just drag the horizontal continuer. Perfect. And we can just delete this blank as of now. Okay. So this horizontal container, I can just give the background as in now as orange. So I will understand like this is a horizontal continer and click on Dashboard. So now the thing is you can either keep blank first. I can just keep three blanks because I want three KPIs. So just drag the blank there, increase the size, and again, put a blank, and again, put a blank. Okay. So this way it will be easy for you and you will understand the pattern we are doing. So that's why I'm doing this. Now the thing is, I have to put three KPI charts, right. So you can see the first is the patient volume. So I'm just confused like which one I should put. I think I'm just putting the bar one because I love that a little bit more. Okay. And then for readmit I'm putting the line graph. And for the average time to stay, I'm also putting the line graph. Okay. Now I can just remove this blank spaces that is there, and I can just click on one of the chart, double click on this line, so to select the full container and just change it fix side to fulfill it right and just think it's a high alta bit. Perfect. Now the thing is we have to remove the formatting in the thing right. So I have to go one by one and right click format. In the right hand side, you can see an option for grid line, so do it none, and same for the other things. So for this as well, I will just go again, click on format and gridline and do it Nunes nun only. And for the last one, I can just click from here only and format and grid linen and zero Linus zero, and Tranno as nun, and for Rose also the gridlines nun. Okay, so now it's perfect. Okay. Only thing is, I have to orange this, so I click fit and standard. And right click fit entire view. Okay. Just remove the fixed size. Okay. So now our Ks are looking much more nicer, like how the patient trend is going on. What I can do is I can also use the line graph in all the three instances, but just wanted to show you like we can use different kind of variation. That's why I'm doing that because whenever we're analyzing data, so it is good to have a line visualization, as we studied. So now what I can do is in this one, I can just add the line pattern, so I can just right click on this and create a duplicate. Control click. And now what I'm trying to do is I'm just remove all the KPIs, change these two circles, and do a dual axis and just synchronize the axis and remove the header. Okay, remove the header. Perfect, and just reduce the size of the dots. So this dot will look much more nicer if we go there. So that's why I just thought to add dots. So in this, it is not visible, so I have to just increase the size a little bit. Perfect. So now if I go, now you can see a little dot, right? I can just increase the size a bit more. Okay. Perfect. And the same thing I can do it here. So just Control click and circles dual axis, and Cytron axis, and remove the header. Perfect. Now, the other thing also we can do is we can also add some kind of variation light. We can also add minimum maximum as you've entered here. So I will just add this standard view. So Marston perfect. Now what I can do is I can also add minimum maximum as we have done in the bar graph, I can also add minium maximum ranges near right. So I'll just go to this sheet. So I'll just calculate calculation and just search for minium maxim this one, duplicate this calculation, and we'll just do the same thing for the other KPIs. So minium maxim for readmitted tight, readmitted percentage. Readmitted patient. This is a percentage, right? Percentage. Now what I can do is I can just write if my readmitted percentage is equal to window maximum. Of the readmitted percentage, then I want green, and I can just copy this and paste it here. And if it is minimum, in my entire window, what is the minium? Just highlight with the red color and click on a fly, click on Okay. Perfect, and just drag this to the color shelf in the second one. Okay. Now the thing is all we have to change the color palette. So for red, I want to give the red. For green, I want to give a green, and for null, I want to give it a transparent as it now. Okay, so I'll just click on drop down and we'll just my transparent color palette. Click on apply, lc on, okay. Perfect. Okay. I can just synthesize a little bit. Okay, perfect. So now if I go back to my so now you can see this little Dt r. So you can see the minimum readmitted percentage was in 2012, and the highest is in 2022, which is alarming stage right in the current, it is like almost 100%. Patients are getting readmitted. So it is alarming situation that the business should look into. And the same thing I can do for this chart. So I'll just create a duplicate again, click on Addit and we'll just do this for days stay, okay. Days stay. And instead of readmit percentage, I can just add dist, and I can just use this as a DST. Okay. I can just copy this paste this. Okay. And what I can do is I can just add like I want to see for the average one. So if the average dt is equal to the window maximum of average dst. Okay, I can just copy this again, paste this again and change from window maximum to window minimum. Okay. Perfect. So now my calculation is valid. Clicon apply, clcono now just drag this one to the second color palette of the color shelf. Okay. Perfect. So now I can see the minimum and the maximum. Maximum should be this, but it is highlighting wrong. Add it. Something I have done wrong. Okay, I have used the patient volume right, so that's why this is showing the wrong one. I have to use the days one, right. So this I have to put in colors. Perfect. So now it is showing correct it. So for the null one, I will just do it a transparent color palette or I can also do the same color palette so it will show the dots. So let me just do that. So null, I will just do the hex code as 55555. Okay, I have to do 555555. Okay. Perfect. And for green color and red red color, right. Apply Okay. Perfect. Only thing is like I have to increase the size a little bit, so it should pop up there. So now I think it should be visible in the dashboard. Perfect. And the same thing I can do it here. Like instead of transparent color, I can just give the color paratus a black color. 555, 555. Okay. Apply increase the size is a bit. Okay. And go to your dashboard. Perfect. All right. And double click on this and you can see an option for drop down distribute content evenly. So it will align all the KPHcharts. Now you can see your KPA looking so much nicer, right, so much cleaner. So now, let us just see in the next video. We'll just arrange other visualization in this dashboard. So I hope you are getting this, how we are arranging this and how we're doing the formatting changes. So if you're liking this course till this part, do give the command box your feedback. I'll be happy to in 29. Designing Dashboard 02: So, welcome back. So now what I want to do is so now you know, we have arranged all the KPHR side. So now our main aim is to cover the table details. What I want is I want to put this table down, and I thought, like to put seasonality above this. Okay. So just a change of thought. Okay. So now what we'll do is we'll just see these two things, seasonality encounter and seasonality encounter by gender, right. And seasonality encounter season also we have, right. So now what I want to do is we want to give the e as a filter, right. So what we want to do is I don't want to give as a filter. So what I want is I want to give it as a Uh, click button. Okay. So how to do so. So what I can do is I can just create one sheet. I can just writes filter. Okay. And what I will do is I will just add this into shape. Okay. And what I can do is I can just see my start one and I can just add into the shape. So can add all members. So this is for all the years and add this to text. Okay. Give it to the entire view. Okay. So instead of text, this is too many years, we have data. So it is not good to use shapes, but if you have only three parameter like 11, 12 tatam or any other category like technology, office supplies and some other thing. So that time, we can use this kind of thing. But as of now, what I will do is I will just use this as automatic. Okay. What I can do is I can just square one. Okay. And teas size a little bit. Okay, perfect. And just do the standard view, entire view. It is looking like this only. And for the labels, I can just do it bold and alignment, I can give it a center line. And a middle. Perfect. So now I can see for all the it is coming like this slide. And I can get the color as more colors. And 555-55-5555. This is my favorite color you know now. So just do it again. 555, 555 and click on Okay. Perfect. So now it's looking fine. So go to hospital experience. So now what I want is I want a filter shef to show first okay. So I just use a vertical container here. So in my vertical container, I will just remove this blank space. Okay. So this is my vertical continer. So I'll just give the layout as of now. So I will just remember, I'm just doing all the things in this. So perfect. Okay. And then what I want to do is I want to give one title, use this filter, click on this button to filter your filter to see the seasonality. So what I want to do is I want to give one text field, okay. But before what I will give is, I will just keep two blanks here in a vertical container. Okay, perfect. Perfect. Now what I can do is I can just use one text field at text, and I'm writing star, select the ear to see the seasonality. Seasonality, based on gender and seasons. Gender and seasons, right? I like this, do it bold, change the height to 12, and you can just change the taboo semi bold and click on. Okay. Now I can remove this blank. Okay, perfect. So now what I have to do is I have to use the ER filter, right? So I can just add the ER filter here and hide the title. Okay. I give the size. Okay. And fit standard or fit with, I will do. Like, I'm not able to see all the things, so I can just remove this blend, and I have to do something, so it should fit in a single line because it is not string. If I do standard, and if I reduce the size a little Perfect. So now you can see this coming in well limelight. So now if I go to my hospital experience, so now it's perfect, right? So I can just do a little bit upward. Okay. And now what I can do is I can just add the seasonality one. So this trend and just height you can move and this is just the distinct count of patient tight. So I can just cite hashtag of patients, so I can just remove the wording a little bit. Click on. Okay. Perfect. Right. So now what I want is I also want to show the seasonality and also want to show the donut chart. So that case, what I have to do is I have to use one horizontal container because I want to show side by side. So what I have to do is I have to use one horizontal container here first, and in horizontal container, I will just change the layout first so you will understand what I'm trying to do. Perfect. So basically, I'm just trying to build a dashboard according to my wish as I'm teaching you, right? So this can be different for different people. So you can also do one thing when you're starting, you can just create a rough sketch in your notebook, like how you want your dashboard to look like, and then you can work upon the containers in tableau. Okay. So now the thing is, what I want is I want a seasonality by gender, seasonality this, and then I want this trend graph to show away. Okay, I will just Okay. Perfect. I can just reduce the size a bit. Okay, so now it's looking perfect, right? So what I can do is I can just write here, like seasonality by seasons. Click on apply and gives the size to Alan bold it, apply. No season seasonality, but you can say seasons only, but I can just write winter or cold. Okay? Or this second gives a legend to just leave it live as it is. And this is like seasonality by gender. So I will just write seasonality by gender. Okay. And same size 12 and bold. Click on apply. Click on Okay. Perfect. So now thing is, like, either I can use male or female, I've used here. So one thing is either I can give legend or I can just use the labels, so I can just add this into labels. Okay. So now the thing is, like, I have to change the color palette. So for summer season, I want to give it a kind of blue colour, so I will just like my blue tail. So I want the summers to look like this light darker, darker blue color. And for the winters, I want it to look like a gray color. Okay. So click on a plan. Perfect. Like, I think this color palette is looking nice. Okay. And same thing I will do for this. For female, I want to give it as a different color I have to give. But same color of shade I will use. I just the apple color palette which I have, so I will just use the female as male as dark and female as light. Okay, apply. Okay. Okay, so I think this is looking nice as of now, but if I want to change, I will just change in future. So now what I want to do is if I want to click on this, this all three visualization must change, okay. So now we'll see that in the next video. So stay tuned, see you in the next one. 30. Adding Interactivity to the Reports: Welcome back. So now we'll see how we can add this to the filter context, right. So before doing that, I want to convert this Pi hat inward do not chart. Okay. So how to do so. So I'll just click on that. So I know you might be knowing how to create it. So as of now, I'm just doing it as entire view. The first thing we have to do is we have to add some kind of calculation like aggregated measures. So it will create an axis, right? So this is the green, green pill, so it will create an axis. So now what I can do is I can just duplicate this green pill. I will create the two pie chart. Now what we can do is the second pie chart, I can do it empty. I can just remove all the things. Okay. Now the thing is what I can do is I can just increase the size of the first pie chart. And the second Pie chart, I can in size, but a little bit lower than the previous one. Then what I can do is I can just take this circle and put it above this. That means we're using the concept of dual axis. I'll just click on this drop down and create a dual Lexis. Perfect. Now what I can do is I can change the color to white. So now you can see how doughnut chart is ready. Only thing is a little bit formatting is show header and write format and grid line and do the zero Linus null, preference Linus null, drop Linus null and accessTisnll, and also the column one, grid inus null. So not soing perfet. Only thing is I can increase some size if I want to. This is the perfect thing. The same thing I want to do for the second one. Okay. Okay, so yeah I can the size fit an entire view. Perfect. And the same thing I can do for this. Okay. So I can just use minimum of one. Okay, or sum of one also you can use any aggregate measure to do so. Then second one. I can just remove all the things change the color to white. And first one size maximum. Second one size a little bit lesser than the Duexis, right? Perfect. Now, the only thing is I have to increase one size because I've used a bite, so that's why it was not pesible. Now this is perfect. Now what I can do is I can just change the formatting a little bit. So just show header format and go to gradin columns and do it as a nun. Perfect. Go to hospital experience. Now it's looking perfect. Only thing is like the size is a little bit higher side, so I'll just reduce the size a little bit. Okay. Perfect. Okay. The same thing I will do for this one. Okay. Let me just check, what is the size of even here. I'll just do according to this till the middle one till before the first one. I'll just do the same for this till the middle one and before the first one. Okay. And now, if I go back to my dashboard experience, yeah, now it's a little bit cleaner. Uh, only thing is like a little bit more thicker it is, so I have to just reduce the size. Okay, I have to reduce the size here. Not perfect. So you can just play along with it. Okay, so now it's perfect for me. Now the only thing is, I have to use this as a filter thing, right? So how I can do that. Okay, so now what we have to do is we have to add some kind of interactivity here, okay. So I'll just hide this label. So if we add some interactivity in a dashboard, so that people will be more flexible and will use the dashboard more often and they will find it more interesting to play around with it if they want to see some kind of pattern, right? So how we can do that is the option for dashboard. We can see an option for actions, just click on it. So we have different kind of actions available to us. That is like filter action, go to sheet, change parameter. Change that values, right? So in this course, we'll be dealing with the filter action mostly. So I will just create an action to change here. To show seasonality. Okay, so I'll just unselect all the things. Now what I want is if I select a e and there are three actions either you can hover over and change the visualization, either you can select or either you can use a hyperlink. So as of now, I'm just using the action on select. Okay. Then what I want is I want to change the three visualization. I want to change the seasonality. I want to change the seasonality by gender, seasonality by season. Okay. And after the selection is clear, I want to show all values, the overall value I want to show. Either I can exclude all values, I can show all blanks. Can use the filtered values, the last filter, or I can use the shoal values, the oral level. Okay. So I just want to use the oral level or the previous filter that is applied, okay? So now just Clicono and Klicon. Perfect. So as of now, you cannot see any change. So once I will click on this, you can see now the trend is changing, right? So you can see now how cool is that. Now you can see the trend this year, 59 percentage of the patient have been dlled in summer and 59% almost same percentage here. But in gender like female are mostly visiting the hospital as compared to male. And if I see for the latest year, you can see all the hundred percent is on the winter season and if I go for one year back, so you can see 60% of the summer and 45% of winter season. So you can see a good analysis you can see, right? So we can play with it. So I'll just uncheck this and this will show me the precurs numbers. Okay. So now, I will just go to the sheet and we'll move the year from here, so it will just show for me the overall level, so now no filter is applied. And the same thing I will just do for all the other things. Okay. This one. Okay. Dashboard. And the same thing I will do for this one because in the previous thing, we were just developing a dashboard, so we are seeing for the one ear, but now it is all dynamic, so we can change it tight. One more thing we can do is we can also add here, the ear which we are seeing. I can just add dash and I can just add the ear upstart. Apply. Okay. Four this year, okay. So I can just reduce the size it a bit and do it 11 or do it at ten. It's not fitting nine. Nine is working. I just use nine as it now. If it is small, I can just change, but as it now, just keep it as nine. So nine and just add the year here at last. Okay, so now you can see the title also changing dynamically, right? So how cool is that? So if I change it, if I remove this, then it'll be like for or level late is checking. Okay. And for this, I don't need to use it. So like I understand only I can do this thing. I can just change the formatting of this. So instead of the full name, I can just click on the format and go to a header and pain go to header. So what I can do here is for the month one, I can just change it a little bit. So as of now, month is a calculation, I believe. So this is the calculation that we have done. That is the month thing. So what I can do is I can just use one more function here, so I can use left function here to trim the first three digit. I only want the first three digit. So like January I want Jan, February February. So that's why I use the left function here. Click on Apply, click on Okay. Perfect. So now it's looking much more cleaner, right? Now we can easily see the trend. Only thing is in this one season one, it will be again, they will not be able to understand how you have filter the group. So that's why group are static and we should not use group. We should avoid groups like wherever we can. So that is the one drawback which I told you in the starting. This is how we don't use group, but just for your understanding, you should know how to create. That's why I'm creating that. I will just do it again. November, December, I will just put in winter season. Okay. And a July to September. I will just put in summer season. Okay, and click on apply. Click on Okay. Perfect. Okay. So now you can see a trend is much more clear, right? So one more thing we can do is we can also add some blank specific if you want to show in the middle. So I can just add some kind of horizontal container. Okay. And I can add some kind of blank here, one blank object. And two blank object. And I can just add this thing in between. Okay. And I can just increase the size. Okay. And it's a little bit. Okay. I like to look more nicer. If I want to look at more cleaner, more nicer, I can just adjust the setting like this. Okay. So this totally depend upon us, how we want to do. I can just do it canta line. Okay. So now you can see, left line was perfect, I think. Okay, so this is some of the way you can do the things. I just wanted to show you. So that's why we should be aware how to use our different types of container. Now let us see in the next video. We'll just try to see how we can add the last visualization that is like the table session. 31. How to use Custom Shapes in Tableau?: Welcome back. So now what I want to do is before deloving into the table view, what I want is I want this three KPI should also change according to the patient type, like encounter type. Okay. So what I can do is I can just add encounter type in my new sheet, and I can just add the encounter class type, and I can just add now in shapes, encounter class type. Okay. And now what I want is, I don't want all the services, okay. I only want to focus my dashboard on ambulatory emergency situation, the inpatient, the outpatient. An ambulatory only four thing or not ambulatory, the urgent care. Like these four I want, for example, the ambulatory wellnes removing as of now, click on Apply, click on and do it the entire. Now the shapes will be like if I click on this, the shape will be something limited to the taboo dashboard. Now if you're working on the real time industry, if you're working on the real time industry, there might be cases like you might be given you have to use some shapes, how to do so. I have some shapes I have downloaded, so I can just copy all the shapes. Okay. Wherever you have downloaded, you can just go to the document folder. You will have one Tableau repository and you have one folders shapes. You can create a new folder customize shape or what I can do is I can just get one new folder here and I can just write hospital KPIs. Okay. I can just double click on it and paste it. I add all the things. So now if I move back to Dashboard and if I click on shapes and if I click on reload shapes, now you can see an option for hospital KPI has a card okay. So now I can give the symbols according to the symbol that I have downloaded. So for the inpatient, this one outpatient, this one, urgent care, this one, Okay, apply. Okay. And size, I can just increase it a little bit, so you can see the size. Okay. Now only thing is I can just add into the labels as well. For inpatient, I've used the wrong image. For inpatient, I can just use double click on it and go to your hospital setting, and this is the inpatient which I want to use. Perfect. Okay. This is how you can use the different logos. Now what I will do is I will just click on the hospital and what I will give is I will just give the filter in the starting, so I will keep on horizontal container, and we'll just use my title there. That I have created, drag it inside it, and we'll just drag the encounter type on the right hand side. Okay. And we'll just do it a little bit size size. Height title. Okay. And fit it into view and I have to just reduce some kind of size so that it should fit in the dashboard. Okay. So just do it a little bit formatting. Okay. So now you can see it is there. Only thing is I have to increase the size a little bit because it is too much minimum. Okay. Perfect. So now also, it is not visible. So what I can do is I can just add it inside the down horizontal container. I can just add it this here. So yeah, perfect. So now, it's like, much more visible. So only thing is, I can just add to tie and double click on this and formatting thing I have to do. I have to just double click on this, double click on this, arrange this it a bit. All the things you have to arrange, continuous container. I have to just drag all the containers that I'm making. I'm just dragging it down by selecting this double line icon, and just arranging it downward. Okay. Now what we can do is we can just add some blanks. Okay. And do it like this. Okay. Perfect. And now I can just add the title in the down. Okay, remove this blank space. Perfect. And size, and just double click and reduce the size a little bit. Double click. Double click and a little bit down. I can just reduce the size a little bit. If I want, I can just reduce it to a little bit so that it will fit. Okay. No fitting perfectly. Now I can just do it a little bit, like low right. Perfect. Okay. The only thing is for the inpatient, it is not coming up, so let me just click on Libel allow labels to word mark. Now what I can do I actually just drag the suchen a little bit far away so the person can see Perfect. So now what I can do is I can just use this filter action. So you can see the filter icon. I can just click on this. But as I will filter all the visualization. But what I want is I only want to filter by these three KPIs, okay? So what I can do is I can just go to Dashboard actions and this filter generated, click on dit, and I will select I want to do. Now instead of all the things, I just uncheck this. I will just do the KPI thing. I want to change the patient volume, readmitted percentage, and the average time to stay, right? Click on Okay. Click on Okay. So if I click on Inpatient, you can see trend is changing right. For emergency, the trend is changing right for urgent care, we have different trend. For outpatient, we have different trend. The thing is like we are facing issue in this one. So you can see the issue is coming in this one. So why it is coming because in the calculation for the inpatient like they've given the encounter classes inpatient, then only it is calculating the readmitted percentage. So that's why we are facing this issue. So if I go back to my sheet and just see my calculation here, you can see this is the readmitted percentage, right. The thing is, uh as if now, I don't want to change this calculation because I only want to see the readmitted rate for the patient who are incoming right. So that's why like this Kp shring correctly. Only thing is, I just wanted to show you like we can also use some kind of logos in tabu. Okay. But this will not be moving forward with. So I'll just cut this and we'll just move back to our original dashboard. And now we'll just try to build our last table visualization and we'll just wrap up the session. So see you in the next one. 32. Designing Dashboard 03: Welcome back. So now let me just go back to tabu. So now the thing is like we have to just add one more visualization that I wanted to show to the stakeholder. That is the map the table visualization, right? So let me just see this is the one. This is not the one. This is the one, right? So I can just cross this icon, and I can just go back to my sheet and see, now, this is looking fine. Only thing is like I just don't want to show the things right. So I can just click on this format extension. And once you click on format extension, it will show you the flexibility to change the thing like I don't want to show the toolbar. I want to show column filter if I want to, but I don't want to show. You can just adjust something. You can also give the button to download the Excel sheet, okay, so they can analyze it. So I can just give dashboard icon. Okay. Perfect. So now it's perfect. So now what about two, I'll just arrange a little bit. Double click and do it above, double click, do it above. Okay, double click and to sit above and double click and we can just do a little bit above. Okay. And now this one I can just add just a little bit. So I can just do it for all the claims, it is not visible. So we have an arrow, so I think this should be perfectly fine, so I can just scroll through this or as of now, it can increase the size to be thousand as if now for my case. Okay. So now if I change the title, so I want to give the title as insurance of payer summary. Okay. And I can just give it the tabu semi bold and I can give the 12 and bold. Okay, click on apply. Click on Okay. Now you can see the person can see for all the peers, right? You can just scroll through this if they want. But this is how we want a final report to look right at. Now the thing is we can just remove all the background, double click on it, go to layout, and remove the border, double click on it, remove the border. Okay. Pun chart, double click on it, remove the border. Right. Perfect. And you can see some kind of spaces there, so I can just remove this space. It's not like working as now I'm just happy with it. So I'll just do it as if now it like this way. So the sizes a bit. Okay. Perfect. So now you can see if I click on the presentation mode, so I can see this is my final dashboard. I can just realign the last structure. So double click on it and just go to layout and give the botersblack. Okay. So if I see your presentation mode so you can see, this is the hospital analytics dashboard that we prepared. So they can see the patient admitted journey, like what is the admission ratio, how the readmitted patients are there current year, and the average number of stays. And on the basis, they can see the seasonality controls that. They can see the seasonality, right. And they can also see the pay summary like how the pair summary is going on. One more thing we can do is we can also change the pairs summary according to the earbs if you want to. But as of now, I don't want to club this. I want it to be at the overall level, so I'll just leave as it is. Okay. So now what we'll do is we'll just work upon in the next video on the tool tip thing, like how to add tool tips in taboo and we'll just restructure something like we want to. But I'm happy with the overall report that we have made. We have made a great progress here. Okay, so see you in the next one. 33. Formatting Changes and Applying: So, welcome back. So now we'll just move on to the formatting things. I'll just go one by one. So go to Tooltip. And what is the most necessary information? I will just keep that I want the year. I want the patient count, and I can just add up blankspacie. And for current year, I don't want in the tool tip because it is shown in the top right in the tax field. And here I change also I'm not interested and many maximum label also I'm not interested in t. So I'm only interested in the here in the foundation of patient tight. So I can just increase the size a bit 11 size, and I can just take the preview, so it is looking like this. What I can do is I can just add here and I can just add one KPI number of patients. Double click. Okay. Now what I can do is I can just highlight this different colors. I can just take as of now, this color and with a bold. Okay. And just let me give you? And do it the same color bold and this color. Okay. And do it bold again. Okay. And just check like how it is looking. Okay, so it's not looking nice. I'll just go back. This is fine, I think, as of now for me. People can see. Okay, so yeah this is fine for me. Okay so just keep like this. So I can do the same thing for the other one. This one I will just go and for all tooltip, only the year and the readmitted percentage you want, right. So I can just see for year and readmitted percentage for her, I can just change it to this green color and make it bold and other thing is perfect, right? Okay. Click on apply. Now, the only thing is like I have to convert this into percentage in the tool tip. Readmitted percentage, this is the one. In the all sheet, I have to see a the readmitted percentage. So I can just click on this format, like default properties, number format, and give it a percentage, and one place decimal. Click on Okay. Perfect. So now it number is coming out to be correct percentage value. Perfect. Go back to your hospital experience. The same thing, we'll just go to the next one. So this one it is your homework, you can just try to clean this up this average number of stays. Okay. We'll just move on to the next one. And we'll just do for this donut chart as well. So for donut chart, I will just click on the A tool tip. I want a month group. Okay. And I want the number of patients. Okay. And what I want is I want percentage of percentage contribution, right? So I can just change it. Click on Okay. If I see number patient 109, percentage contribution is 71.2 percentage. So this is looking nice as if now for me. Only thing is I can just change this month group to be a green color because we are being consistent. Click on Okay. Perfect. Okay. Same thing you can do for this. Same thing you can do for this. All the formatting you can do for this, this, and this is your homework. You can just try to practice it, it is a simple thing. In the last one, we donate tool tip, so I will just go to the sheet and tool tip I will just remove because this is a table format so people can see the visualization and they can understand. This is the perfect thing. So what I can do is I can just keep this donut chart right hand side if I want. So it will look the reporter will look like much more nicer or cleaner. Now what I will do is I just save my file. So I hope you were able to understand how we can do tool tip is so necessary, and this will add a more context to your dashboard, so you can work upon it. To make it more meaningful, you can just change some wording and all. You can also inside tool tip inside a tool tip. So let me just show that for you. For example, if I want to add seasonality in seasonality, I want to add average R stay. Okay. So what I can do is I can just go to this at tool tip. There's an option for adding an insert. So if I click on insert, you can also add the insert sheet. So as if I can insert the average time to stay. Okay, I can just change the height to be 600 and this to be 600. Okay, and click on Okay. If I go back to my dashboard and now if I overw you can see for June month for my month, you can also see the trend line how it is going, average number of stays. I also filtering in the a visualization. You can just play with it. Just wanted to show you one other quick feature, which is available, but we have not covered in this course, so you can do that click on Okay, I will just remove that. I hope you have learned a lot during this course, and we are just almost near to the end of the course. So please give the feedback if you love going through this and you've learned something from and it was an add on to your career path. So see you in the next video where we'll wrap up all the session and see where all you can go after taking this course. Okay, so see you in the next video. 34. Final Report: Summary of Analysis: So welcome back. So we have created a dashboard. So now you can see how much insightful it is. So if the stakeholders sees, they can see, what is the patient admitted things here over here. They can see, what is the readmitted percentage. So you can see readmitted percentage is going to 100%, so that might be the alarming stage, right? Like the patient are getting readmitted again and again, so they are not recovering fast. So the business, like the healthcare business should look into this hospital, like what is going wrong. And for the patient admitted, you can also see the trend. So for the patient admitted, as if now it is decreasing, right? So that is also the concern why the patients are not coming to the hospital, like not enrolling in the hospital or might be a good sign also, like the people are in good health, but there can be also an alarming stage because people are not recovering and the mortality rate is high that we saw. So that's why people are not coming to this hospital. Then the average day we have seen. Then you've also seen the seasonality for year over year. And we can see mostly it is for summer and winter season, it is mostly the same. Only for the later part of the year for 2018, 2019, the summer, the patients are coming more as compared to the winter season, and the female population is coming more to this hospital. So we have more female number of patient as compared to the male patient. We have seen that. And regarding the payer information, like we have seen, like for the Medicare and the blue cross shield, they are covering the most part of the claim. And the other partners of the insurance company, they are not performing, good, we have to pay most of the percentage of the cost from our pocket whether or not, we have enrolled in this program. So that payer we have to see not performing well, so I can just change this to payer name. So that is alarming stage to see that. And this can also be a good symbol to analyze claim which pair partner is best for the business so that we can tie up with. So this is the basic analysis like the CEO can take and they can work upon this inside to fulfill the patient like hospital performance to increase it to one level up, right. So this is a very good KPA dashboard that we have created. So I'm just very happy to share with you. So I'm just happy that you have made it so far. So you can also share this kind of project in your LinkedIn to increase your network growth, and you can also add as an portfolio project in your Tableau public, and you can just showcase to your audience. So this is a good start that you have done in tabu, and I can assure you that you are ten steps ahead of the people who have not started the journey in tabu. Those who know tableau, they also don't know some of the advanced features that we have covered in this course, so you're one step ahead of them. Give a pat at your back because I cannot give it. Congratulate for making to this far. See you in the next course in future. If you are happy with this course, you can just give your comment, all your feedback. I'll be happy to work upon it, see you in the next one. Till then, happy visiting. Bye bye.