Tableau Masterclass: From Zero to Hero

1. Tableau - About Course: In this video course, learn tabu and its concepts. Tableau is one of the most popular business intelligence and data analysis tool. It was founded in 2003 and used not only in data analysis, but also in data science. Will Tab easily visualize any data, connect different sources, easily explore different views, and even combine multiple databases easily. Create custom calculations to enhance your analysis, also blend and sort the data easily with Tableau. We will learn how to work with tabu desktop in this course. Tableau desktop delivers everything you need to access, visualize, and analyze your data with a drag and drop experience. In the end, we will create interactive dashboards and also forecast with Tableau. In this course, we have covered the following lessons with live running examples. Let us start with the first lesson. 2. Tableau - Introduction & Features: In this lesson, we will understand what is T, it's introduction and features. So let us start. So T is a BI tool that is a business intelligence tool that allows you to analyze the data to create visuals. And with that, you can also easily create dashboards and share it. Tabu was developed by Tableau Software, and it enables users to create interactive and sharable dashboards that display data in a visually compelling and understandable way. Okay, it also supports various data sources. We Tableau, you can perform real time data analysis to monitor trends and make quick decisions. Easily create reports for business performance and strategy. Okay, you can also visualize financial data, analyze market trends and consumer behavior, and it is also used in data science. So in this lesson, we will discuss the following topics. That means the process of data analysis. Since tabu is a data analysis tool. Tab is also a BI tool, so we'll also discuss what is BA, that is business intelligence. Then what is and the features of T. So let us start. So your data analysis process includes data preparation to begin with. Okay? And the role of a data analyst is quite important these days, even if the organization is at a smaller scale or even at a larger scale. The key is to understand the data and get valuable insights from it so that the performance of a company can be tracked, which in turn will help in scaling the organization. The first step is data preparation. Okay, it means cleaning the data, removing the duplicates, transforming the data, fixing the missing values, so that the data is ready so that the data is prepared. The data preparation step takes the raw data and converts it into useful and easy to understand information. Okay, that also includes fixing the wrong data. Okay. The next step is model. When the data gets ready, it will be modeled. In this step, we will understand how multiple tables are related to each other, so we can create relationships between them. The next step is to visualize. Okay, we all know that if we are given some text or some graphs, which one we will like? Obviously, the graphs and charts. It's quite easy to understand. This step will bring your data to life, and it can be represented in the form of reports so that the reports can be analyzed and better decisions can be taken. Then comes your analyze. It means to find the insights to identify the patterns and to predict the outcome. Okay, through this step, the business decisions become easier. Next comes your management. So if you're the data analyst, you need to manage the reports, dashboards, models and share it with others with your team members or colleagues. You need to completely supervise this process so that the reports and dashboard can be easily shared with your team members without any hassles. Next is business intelligence. That is BA. So I just said that Tableau is one of the top BI tools. So what does business intelligence means and why it is so popular these days? To analyze the data and to display it in a way it speaks in the form of charts, graphs, and later on dashboards and reports is what we call BA. Such data is very easy to understand and any team member or the founders or the VPs can easily understand so that they can track the performance, scale the business, forecast the business, so that your company is ready for any kind of market change. Some components I would like to discuss regarding business intelligence first to begin with, to collect the data. So through, you can connect more than 100 data sources like your Excel, SQL, CSU files, and others. Next comes your data analysis. Okay, we already discussed that it means the techniques to identify trends, patterns, and correlations within the data. Then to visualize the data in the form of charts, graphs so that you can easily create reports and dashboards later on. Then comes your insight generation. Okay, the results of the above analysis is interpreted so that opportunities can be identified. Now let us see what is Tab. Consider it as a data analysis tool through which you can easily transform your raw data into actionable insights through interactive dashboards, which you can later on also share with your colleagues and team members. With Tab, you can easily improve your decision making capabilities, track the performance of a company. Okay, easier to communicate and collaborate. You can easily share your reports and dashboards. Perform data analysis, and you can easily understand your data and insights. Tabu was founded in 2003 by Tableau Software, and it was later on acquired by Sales fortune 2019. Now, here are the features of T. The first one would be data connectivity. You can easily connect multiple data sources. Like if you have your data in an Excel sheet, you can easily add it to T. Even your external data or if your data is in the form of Kill database, then also you can easily connect it with Tableau. Then comes blending the data, that means data blending. You can combine data from multiple sources, so that the analysis is comprehensive and easily understandable. Tableau is a dragon drop interface. Drag and drop fields in the form of rows or columns, and you can easily visualize your data in the form of different charts like line charts, histogram, Pi chart, and others with just a drag and drop interface. With, you can easily create dashboards with the real time data so that if the data is updating frequently, you can easily take the decisions time to time. Then comes your customization. You can easily create and customize dashboards and reports. It's like a dragon draw feature only. Customize them accordingly. Easily place your charts and reports in your dashboard. Easily customize them. Then comes your geospatial data. Easily create maps, and easily create maps which are interactive, and Tableau supports geospatial data. Tabu also offers cloud based analytics so that you can easily share data driven insights so that users can easily manage and share insights. So, guys, we saw what is Tab? What is business intelligence data analysis process, the role of a data analyst, as well as what is T and what are its features. Thank you for watching the video. 3. Types of Tableau Products: In this lesson, we will understand the different types of tableau products. You must have heard about Tableau desktop, Tableau Public, Tableu Sera. So let us see what are these and what are the different types of tableau products. With that, we will also see that which one of them we'll be using in this tutorial. Let's see. So tabu includes a lot of products. The first one will be tabu dextro. It is used to visualize your data so that you can easily create different charts, graphs, and later on reports and dashboards. So this comes with a trial version of 14 days. So easily use Tableau for 14 days, and later on, you need to purchase the license. So in this tutorial, we'll be covering the Tabu dextro version. That includes all the features of T, but is only available for 14 days. Through Tableau Dextrob you can easily connect to various data sources, and it offers drag and drop functionality to provide advanced analytics capabilities. Next comes your Tableau Public. So it is a free version of Tableau. But whatever you'll create with Tableau Public will be available for public. That means open to the public and you cannot keep it private. Okay, it is free to use, but it includes some of the features of the Tableau dextro version. Next comes your Tableau server. So it is basically a platform for sharing your dashboards and managing users within an organization. It is basically used to share across an organization, allows users to publish dashboards created in tabu Dextra supports collaboration and data governance and enables real time data updates. Tabu server provides a secure and scalable environment for hosting and sharing Tableau dashboards. Consider Tableau server as a platform to share and collaborate. Next comes your Tableau online. It is a cloud based version of Tableau Server. It provides the same sharing and collaboration capabilities as Tableau Server, but without the need for an on premises infrastructure, it is managed by Tableau ensuring automatic updates and scalability. So let us compare it with Tableau Desktop. Tableu Dextro is a desktop application, whereas Tableau Online is a cloud based service. Tableau Online just like Tabusera is focused on sharing and collaboration. TabauOline stores data in the Cloud, and it is accessible from any device with an Internet connection. We will also discuss the differences between Tableau server and Tableau online because they are similar, but Tableau Online is managed by Tabu while TabuServer is managed by your organization's IT team. Tableau Online is a cloud based service while Tabu server can be deployed on premises or in a private Cloud. Now, let us see tabu Reader. Tableu Reader is a tool for viewing and interacting with tabu dashboards offline. It allows users to open and interact with the visuals created in tabu Desktop without needing the Tableau server or Tableau online. So guys use Tableau desktop if you need to create and design data visualizations. Use Tableau reader if you only need to view and interact with the visualizations. Then comes your tableau mobile. Mobile, I guess, you can easily understand an app. Okay? It is used to access tabu dashboards on your mobile devices. It provides a mobile optimized experience to view and interact with dashboards on the go. Let us see what is tabu prep. It is for data preparation and cleaning. It offers a visual interface for combining shaping and cleaning data, making it ready for analysis in Tableau dextro. The last one is tabu Cloud. So the Tableau Cloud is a new name for Tableau Online. That means Tableau Online was rebranded to Tableau Cloud. It offers all the same functionalities as Tableau online, including the ability to share, collaborate and interact with Tableau visualizations and dashboards via the Cloud. So, guys, we saw what are the different tableau products. And guys, in this tutorial, we'll be working on the 14 day trial version of Tableau desktop so that you can understand how the entire tableau works because Tableau Desktop is the product that includes all the features of Tableau. But it is a trial version for 14 days. After that, you need to purchase a license. So in the next lesson, we will install the Tableau desktop on our Windows devices. 4. Tableau vs Power BI vs Excel: In this lesson, we will understand the difference between Power, and Excel. We all know these three tools are really important. Excel came first, then came W, and then Power BI was launched. Let's see. Okay, as I told you before, Excel came before both Power B and W and Power B is a recent introduction to Analysis and BI. Okay. Data visualization, all three of them works great for creating charts and graphs. Okay. But as we all know, Excel only creates simple data visualization as compared to Power B and W. The best of the visualizations are considered in Tableau only when we compare it with Power B and Excel. Okay? You tableau is written in the following languages, including Python and Java. Your Excel because it dates back to even before 1990 when there was no Java and Python. Okay, it is written in C plus plus, Objective C, and other technologies. Power BI is written in Python M and Dx. That is Data Analysis expressions. Your PowerBI is unavailable for Mac. You can still go to our web browser on Mac and work on it, but it is unavailable currently for Mac. Tabu and Excel are available for the three operating systems, including MAC. Excel V only developed by Microsoft. PowerBI is developed by Microsoft. But Tabu is now owned by Salesforce because Salesforce acquired Tableu software. Power BI is cheaper than and Excel is cheaper than both Power B and W. The cost of Tableau also depends on the organization. If the size of the organization is very much scaled, then Tableu would be more costly. Okay, processing of Power B and T is quite quick and far better than Excel. We all know that What will happen if you load large amount of data on Excel. Let's say you created an Excel file with lots of rows and columns, then loading issues can occur. Then data analytics capabilities. Excel is not better than T and Power BI, we all know. The analytics capabilities of Power I and T is quite good. But still, it is considered that T wins the race in the analytics capabilities. Reports Excel is having limited capabilities in report creation. Okay. So reports are more interactive when you work with Power B and W. When we analyze dataset, I just give an example of Excel file. Let's say you have heavy Excel files, large Excel files with lots of rows and columns, then Excel may create issues. Okay. But Power B and T easily supports a lot of different formats, and even if the file is huge, there won't be any such problem with Power B and W. Enterprises generally Excel is preferred by small enterprises, and Power B and T are mostly preferred by large enterprises. Power BI is also software that can be used by small enterprises. Okay. So, guys, we saw the difference between one of the top three tools for analyzing data, creating visualizations, creating reports. Thank you for watching the video. 5. Install Tableau on Windows 10: In this video, we will learn how to install the current Tableau version on Windows ten, open the web browser on Google Type, Tableau Desktop. We will install the same version because it comes with a 14 day trial. Here it is Tableu Dektop. Click on it. Now when you reach here, it is written, start a free trial. So this is what we'll be installing. So for 14 days, Tableau is free. After that, you need to pay. Click on it. Now you need to fill your details. Okay, let us fill Okay, you can use any of your email ID. Also add your country and phone number and click Download Free Trial. Now to download started. Here it is 591 MB. Let's wait. The EXE file downloaded. Now right click and click Open to begin the installation. Minimize. Now the installation started. Click here, I have read and set the terms. Now click Install. A Now, guys, the setup installed. You need to restart the system. So let us restart. I'll click Restart now. So, guys, we restarted the system and you can see that desktop shortcut is visible. You can either click here or go to Start and type W here it is visible now. Click Open to open it for the first time. So, guys, Tableu opened, you can activate now. Use Tableu for 14 days without restriction. After that, you need to pay, but we'll be directly going for the trial version. Now enter the same email ID. Click Register. Registration completed, click Continue. So we are inside a Tableau. We opened it for the first time, and we successfully registered it. So, guys, we saw how we can download and install the tabu desktop version that comes with a 14 day trial. So a trial begins now and it will end after 14 days. After that, you need to pay. Thank you for watching the video. 6. Install Tableau on Windows 11: In this video, we will see how to install the current Tableau version on Windows 11. Let us see. At first, go to the web browser on Google Type. Tableu desktop and press Enter. So we will install the Tableu Desktop version that comes with a 14 day trial. So I'll click on this link, table.com, and it will automatically take us to the Tableu Desktop link. Here, you can see start a free trial Link is visible. I'll click on it. Now you need to add your details. It's written Tableu Desktop is for a 14 day trial. Okay, not a problem. I'll add the details now. And Okay, so we have also added the phone number. Now click Download Free Trial. Here it is the download started. Okay, 591 MB. Let's wait. The EXE file download it. Right click and click Open, minimize the setup started, select this. I have read and accept the terms of the license agreement. Okay, click Install. I So, guys, we have successfully installed T, and it is opening now. Here, the trial version is visible. Start your trial for 14 days. I'll click here. Now, add the same email ID. We added our company's email ID. Okay, click Register. It's written now you can start using the product. Click Continue. So, guys, we opened Tableu for the first time. Okay. Here, options are visible to connect your data source. It can be an Excel file, even a text file, JSON file, even a PDF or two different databases also. So on the left bottom, you can see the sample superstore provided by Tableau only. Okay. And here you can see some pre built templates. So guys, we saw how we can easily install Tableau on our Windows 11 system. In the next lesson, we will see how to connect our data source. Okay, we will connect an Excel file. Thank you for watching the video. 7. Connect Data Sources in Tableau: In this lesson, we will learn how we can connect data sources in T. So we already installed T. Now we will see how we can connect various data sources and how many sources are available. With that, we will also see how to get the data from an Excel file. Let's see so with tabu, we can easily connect over 100 data sources. But you would be wondering that from where we'll get our sample data, which is perfect. So you don't need to worry about it. Okay, so when you open Tb, you'll be having some sample data, which is already placed on your system because you installed tabu previously. When you open Tab, DktopO the left, you can see some options. So these data sources you can easily connect. We will see how we can connect and import a data source in W. But before that, we will also understand this live and extract option. So when you open T, you'll get this option on the top right. We'll see it later. So you will be getting an option to connect with live connections or data extracts. Okay, so let us see the difference between live and extract. Live connections, as the name suggests, includes real time data. So if the data source will change, it will get immediately reflected in T. Since it will provide real time data, the performance may get affected by the network speed and traffic. Then comes your data extracts. It is having faster performance because this mainly includes the snapshots of data optimized before. Okay. You can also access it offline because it is not a live connection and it is not real time. Now, let us connect a data source. We will open and we will connect with the sample data. So where you can find the sample data on the left bottom, there are some saved data sources. One of the files will be accessing, and the file name is sample hyphen superstore dot excelX. I've also provided a link here. You can see under the documents, you'll be having a M Tableu repository. And within that, you'll be having a data sources folder, and your Excels file that is your sample file is available there. So let us open our tabu after installing. So we already installed Tab and to open it, you can click on the Desktop shortcut or you can also go to Start and type Tab. Since you installed it, it will be visible here. You can open it from here, click Open or click on the Dektop shortcut. I'll click on the Desktop Shortcut. If you remember, we installed a trial version of tabu that is Tab Desktop. So you just need to click on Continue Trial now. And here is your tabu. Okay. On the left, I already told you that you'll be having your Tua file and Tao, so these are the data sources. You can connect your tableau with Excel, even a text file, a JSON, even a PDF file or even your geospatial data. That is spatial file. With that, you can also connect databases. I'll click More here, let's say. And here you can see all these databases you can easily connect. Okay, I also includes your MIEQL Mongo DiecL I just click the Escape key to close it. Now on the left, I told you already Tableau provided a sample superstore for you. Okay, so I'll open this. Before that, you can see quick start. Some prebuilt templates are visible. You can check here. If you want to open your own Excel, you can click either here or either here, open a workbook. So this is the place wherein all your projects will be visible W. I will get listed here. These are the safe data sources I already told you about the sample hyphen superstore Excel file. You can directly click here and start, but I'll also show you the location, so I'll click here, Microsoft Excel. Okay. So here is the path, documents M tabu repository data sources version and the following. Within that, you have your sample dataset. Just click here and click Open. Before that, I'll just copy this and I'll just paste it here. Press Enter and here is your path. Okay, I told you see users documents tab repository data sources. So this is our file, Excels, I'll click here. Okay, so this was the path and the same file, click here, click Open so guys, we opened a sample superstore Excel file. Here it's visible and on the left, orders people and returns. A the tables or you can say the sheets. It is empty here. You need to drag tables here to create a data model. So we will drag orders here. Okay. But here you can see data source is visible. So data source will have all these details. Sheet one is the place wherein we will create our view and work around Tableau later on. Okay, this is to create a new worksheet. This is to create a new dashboard. We will see all these things later. Okay. Right now, before moving the orders table here, I'll first check the sample Superstore. So I hope you remember, this was a sample Superstore. I'll open it. And this is our file. So this data is having ID, date also, order date ship date. Sting also, that is ship mode, customer name, customer country customer details, city state postal code with that customer ID also. And I'll move further region details, product ID, category, subcategory, product name, and other details related to sales and all. Here it is. Okay, sales quantity, discount profit. And herein we have our orders sheet, then we have our people, and then the returns under the returns sheet. So we will track the orders sheet. So this is having all the data types. Data type is a type of data that actually distinguishes your records. Okay. So we have date numbers. Okay, numbers here, postal code, we are also having string. So this is perfect. I'll click Close. Now, we will move the orders here. It's written drag tables. Let's see what will happen. And your order table is visible here. I already told you about the live and extract. Okay, what is the difference? Connection is live right now. Live means real time data. So these are the details. What I'll do, I'll just drag it here and it's written. There are around ten k rows. Okay, 21 fields, 21 columns here, and 100 of them are visible here. If you'll type, let's say 400 here, it will display 400 rows. If you'll type more than 10,000, let's say I'll type 12,000 and I'll press enter. Let's see what will happen. It will show you 10,000 only. So here in above the field name, your data type is visible. This is for sting. Okay, date. This is for sting, ID number. Okay. I'll move forward. Okay, then again, sting and sting. So this is your number data. That's why it's visible like this. Also, you can see the globe here. So this means your location, state, province, country, region, city, postal code. Okay. And it's also visible here on the left in the bottom, you can see. So these are the details, guys. We are under live connection, and it is asking us to go to the Set one on its own. With that, the number of rows and columns in the table is also visible. I already told you. Okay, let's say, I'll type 500 here and presenter. Now 500 rows will be visible here. Okay. Now 500 rows are visible. Okay, these are the options to sort the fields. I'll keep the default data source order. So these are the live and extract options. I already told you live is real time data and extract are snapshots of optimized data. Live is dependent on your network speed and traffic. That's it, guys, we connected a datasource. Okay, so we can also go to file and save our project Save As. When you click Save As, it will get saved in the following location under workbooks. And remember, the extension would be dot TWBTbu Wbook. We are not saving it right now. We will save it in our next lesson when we'll be starting with the Sheet one. Okay, guys. So, guys, we saw how we can connect a data source. In W, we connected our sample superstore file. It is already provided by T. Thank you for watching the video. 8. Create a Line Chart in Tableau: In this lesson, we will understand how to create a line chart in tabu. So we already connected the data source, that is the sample superstore file. Now we will create a line chart using it. Let's start. So we will first understand what is a line chart. If you want to display the trends over time, you can use a line chart. I've also shown an example. Okay, it consists of a series of data points connected by a line that shows the relationship between two variables. For example, what we'll do, we will create a sales trend line chart in Tableau. But before that, we can also see another example. Okay, let's say you want to display the monthly sales of a company over a year. So for the X axis, that is the horizontal axis, we can take months from January to December. For the Y axis, that is vertical, we can take the sales. For the data points, we can add the sales figure for each month. That is connected by a line in line chart. Let us create a line chart, and I told you that we'll be creating a line chart for sales trend. This will represent the sum of sales over the years. Let's see. So, guys, we already installed Tabu and we added this data source in the previous lecture, sample Superstore provided by Tableau only, and we have these sheets in it, orders, people, and returns. We also discussed the live and Extrat and the data ties for our orders sheet which we dragged here. Now we need to create a line chart for that. Click here sheet one. Now, a sheet one is visible. On the left you can see the fields related to our orders sheet from the sample superstore. Before 2022 version, here the fields were divided into dimensions and measures. Now it's not visible. If you want to display it, you can just try to drag. Let's say, I'll try to drag the ship mode. And when you drag, you can see now dimensions and measures are visible below, right? So this automatically shows that which are the dimensions and which are the measures. Also, you can see the data types on the left, for category, we have strings, ABC is visible. For postal geographical, a globe is visible. Okay, for order date, date is visible. For discordant profit numbers are visible. Okay, so here is the layout. This is called a shelf. That means this is the column shelf, and this is the rose shelf. This is the mark shelf. So we have some options to add the size and color of the chart, let's say, tooltip also. This is the filters shelf. We will discuss all of them later. This is the Show button if you click again. Okay. Now, these are all the charts visible. And under the charts, when you'll click on any chart, let's say you clicked on Pi chart. Blow, it's visible what you need to create it. One or more dimensions or one or two measures from here, that means. Okay, so this is a hint you can consider. Drop field is visible here. You just need to drop the fields here, or you can also drag it under columns and rows, or you can also drag it under the marks or filters. For filtering, you will add here. Okay, for different options like to create a line chart, bar graph area chart, you can select them and drag it here. First, I'll rename it. To rename it, you can right click and click Rename, or you can also double click. So I'll just rename it and type line chart. That's it. Also, I'll save this book Gudo file, save as. I hope you remember it will get saved under the workbooks folder, so I'll name it Ahmed underscore, T Underscore visuals. So all my line chart, Pi hat map Treemap will get saved here. Ahmed underscore underscore visual dot TWB. Click Save. Okay. Now we have saved it and it's visible here. Now let us create a line chart. But before that, I told you about the dimensions and measures. Let's say you drag any of the field and dimensions and measures are visible. Now, what is the dimension? You can consider it as a qualitative data. Okay, it includes your customer names, product categories, geographical locations. This describes your data rather than measure it. And your measures now measures is a quantitative data. Consider dimensions as qualitative data and measures as quantitative data. That's why it is having some of sales, some of profit here. It includes your metrics and values. It is used to perform calculations and aggregations, such as total sales or average profit per product. They contain numeric data that can be measured and aggregated like averages and others. Now we have understood the layout completely. I'll show the difference between this later on. Now, what I'll do to create a line chart I'll drag the dimensions. That is one of the dimensions, order date to the column shelf. Order date to the columns shelf. Now it is not complete. Drag the sum of sales, sum of sales, if you remember it was under measure. For measures, I'll drag sum of sales to rows. Now you can see line chat created. X axis displays the order, dates categorized by year, and Y axis displays the sum of sales in thousands. Here it is. So this is the area called a view in Tableau. Now on the right, it has also given us the hint, zero or more dimensions, one or more measures. This is what we did, and the chart recommendation is also visible. Okay, line chart. Now this is the view standard entire view. So when we'll create more charts, we will understand this more. I'll click Entire view and you can see it expanded completely. Okay. But we will add it to standard only. When you keep the mouse cursor here, you can see the year of order date as well as the sales for that particular year. So this is how we can create a line chart, and we named it line chart. L let us save and let us see the location. So if you remember we were here, this was our Samba Superstore, so you need to click here, datasource. Then the MITbRpository, click workbooks and here is your file. We just created it amid underscore visual dot TWB. So we already saved it. What we interpreted from this line chart that there was a slight dip in sales in 2022, here it is. Then sales saw a significant increase starting from 2023, reaching over 700 in 2024, right? This line chart effectively displays the sales trends over the specified period, highlighting the growth in sales. In this guys, we can create a line chart in W. Thank you for watching the video. 9. Create a Bar Chart in Tableau: In this lesson, we will understand how to create a bar or a column chart in Tableau. First, we will understand what is a bar chart and a column chart. Then we will create it on Tableau. Let's see. So consider bar chart as a chart to display data using rectangular bars of different heights or lengths. So here is an example. Okay. This shows the sum of profit across three categories, furniture, office supplies, and technology. The bar represents categorical data, right, and the height or length of each bar represents the value or frequency of each category. So here we are displaying the sum of profit across categories using a bar chart. So this was an example. Let's say another example. Let's say you want to compare the sales of four different products. So in a bar chart in your xxx, you can place the product names in YXs the sales and the bars will display your sales figure for each product. Okay, higher the height would mean more sales. Now, let us see what is a column chart. Bar chart and column chart are somehow similar, but in column chart, you have vertical bars. Okay. That means the data is displayed as vertical columns of different heights. The columns here in the image represents categorical data, and the height of each column will display the frequency of each category. In this image, the office supplies is having more profit right. Here's another example of column chart. Let's say you want to compare the students enrolled in math, science, history, and English courses at a university. In that case, you can add X axis as course names, all the four courses, Y axis as number of students enrolled, and the columns will display number of students enrolled in each course. That means columns of different heights. Now we will go to T and create our bar and column chart. This was our tabu under the project amid underscore Tu underscore visual. Okay, we added a line chart before. Now I'll click here. It's written New worksheet, you can see. I'll click on this and a new sheet is visible. I'll name it bar and column chart. Would be fine? Okay. Now let us create. For our bar chat, I already told you, we will visualize the sum of profit across three categories for nature office supplies and technology. For the dimensions, we will drag category to the Rose shelf. Here is the category to the Rose Shelf. And sum of profit that means the following to our column shelf. And it automatically created a bar chart. Okay, it's not quite visible, so you can change the view, entire view. Look, it's now completely different from other view, fit height, fit width, and your standard. Okay. I'll keep it standard. Okay, now you can see on the right, you have the recommended one for horizontal bars. You need to have zero or more dimensions and one or more measures. And this is what we did. It is automatically showing us the bar chart. I'll click Show me to remove it so that I can view it completely. Now, I'll click Entire view. It's up to you what you like. Okay. Now you can see we created a bar chart displaying the sum of profit across our three categories. The X axis, that is the following displays the sum of profit in thousands, ranging from zero k to 150 K. And what is visible under our YX, it lists the categories, these three categories. Okay, so it displays that technology is having the highest profit. Keep the mouse cursor and find the data. Okay. The lowest profit is for the category furniture. So this chart effectively compares the profit margins across different categories, making it easy to identify which category is the most profitable. You can go to File and click Save. Now, we will create a column chart. So our column chart will display categories in a vertical form. That means the chart will visualize the sum of profit for the three categories, X axis will represent the categories and YXs will display the sum of profit. So completely opposite. For that, you also have an option here, swap rows and columns. So I'll just swap it. I'll click on this option, and you can see now what I told you for a column chart, we will represent the categories in Xxs Here it is three categories, and profit would be for YXs. That means 150 K. Keep the mouse cursor and it's visible. Furniture is showing a profit of 20 K. Office supplies 126 K and technology category 146 K. This compares the profitability of three categories, highlighting that technology category is more profitable. So, guys, we saw how we can create a bar and column chart in tabu. Thank you for watching the video. 10. Create a Pie Chart in Tableau: In this lesson, we will understand how to create a pie chart in T. First, we will see what is a pie chart, and then we will create it in Tableu. Let's see. A Pie chart is basically a circular graphic that is divided into slices. As you can see in the image, it is basically a circular graphic that illustrates numerical proportions. It is also known as Pi graph or circle graph. So I just told you that it is divided into slices, right. Consider that each slice represents a category and its size will display the items proportion to the total. So when we'll see the example, the things will be more clear. So here you can see a circular graph with slices in different colors. We can also take an example quickly. Let's say we have divided four sports into what students like. There is a group of 100 students and 45 like cricket, 25 like football, 15 like hockey and 15 like tennis. If you'll be having a pie chart, it will represent all the students in total, right, 100 students, and each slice will represent each sport. That means there will be four slices. And the sizes of the slices will be proportional to the number of students. That means out of the four slices, the biggest one would be for cricket because it is having the more number of proposion. That is 45 students out of 100 students. So let us now go to and create a Pie hat. So this was our T. We already connected the sample store Excel file and we saved the project as Aminco Tb Underscore visual. Good plus, and I'll rename it by double clicking. Pie hat. Okay. All letters create a Pie chart. So we will create a Pie chart to display the distribution of profit across segments. Each segment would be color coded and labeled according to its category, and the size of each slice will represent the sum of profit for that segment. Now to create a pie chart, we will drag the dimensions and measures to the mark stack. But here, under automatic select Pi now I'll drag the segment dimension to the color. Then I'll drag the segment dimension to the label so that the segments are also visible. After that, I'll drag the profit to the size. Click to Entire View. When you'll keep the mouse cursor, it's visible, the segment and profit, but I want to show it as a label. Just dragged profit to label, and here it is. So we have created our pie chart. And here, the legends are visible. That shows the sum of profit for all three. And it shows the legends for the segments. If you want to edit the colors, you can click here and click Edit Colors and you can easily adjust. Okay. So in this way, guys, we can easily create a Pie chart. The pie chart displays the distribution of profit across these segments. Okay, each segment is color coded and labeled according to its category. So this is what we achieved. And the size of each slice represents the sum of profit for that particular segment. So this pie chart visually compares the profit distributions of the three segments, home office, consumer and corporate, making it easy to see which segments are performing better in terms of profit. This pie chart provides a clear and concise way to understand the relative profit distribution among the different segments. So, guys, we created a pie chart in T. Thank you for watching the video. 11. Create a Map in Tableau: In this lesson, we will create a map chart in Tab. Consider map chart as a map only. Okay. First, we'll understand what is a map chart. Then we will create it in Tab to display sales data across different states in the US according to our sample store data. A map chart is a type of chart that uses maps to display data. It will combine your geographical information because it is a map. Okay, I will combine your geographical information with statistical data to illustrate relationship trends or patterns. Like in the image, we are showing the sum of sales. So the darker color is displaying California. That means the maximum sales is in California. And in this way, we can represent a map. Let us see another example. So let's say we want to display the population density of different states in India. Okay, so your map will display a map of India that will display the state colored or shaded according to its population density, and there will be different ranges of population density, let's say, low, medium, high, and very high. So zero, 200 people per square kilometer will be under low density, that is light blue color, and the maximum will have the red color, let's say, that is very high density. This is just an example of a map chart, but we will be displaying the sales data across different states in the US because our sample data is sample store data provided by table only. Let's see. So this was our Tableau. We already saved it as Amith Underscore Tableu Underscore visual, and we input it the sample Superstore. Now let us create a new worksheet, my clicking here, and I'll name it Map. Okay. Now we will create a map. We will visualize sales data across different states in the US. Now we will drag our dimensions and measures. Since we are displaying the sales based on state, so we will drag the state dimension. That is the following to the detail under the mark shelf. Okay. I'll drag to detail. Now you can see the map is visible and it generated longitude and latitude coordinates to plot the state. It's visible generated. That means we did not drag it. We just drag the state here and it generated on its own. Now we will drag the same state to the label pane. And after that, we will drag the sales measure. Here is our sales measure to the color pane. Okay, here it is. Okay. Now you can see nothing is visible because we have 59 unknown values. Just click here to fix it. Edit locations. It is biodefult India because I have this tableau account, the trial version in India, so I'll just fix it by clicking here, United States. Okay. That's it. Click Okay. No, it should be visible and you can see Map is no fixed. The sum of sales are visible. If you remember I told you that the darker color will have maximum sales. So you can check on your own. The maximum sales is for California. Okay, you can use the mouse and control to minimize or maximize. And color you can also change if you want, you can click here and edit colors, and you can change the color from here easily by clicking here, I'll keep the default. So we created a map of the US based on our data. The lighter color is for less sales and the darker for more sales in a region. Here it is visible. Let us do the changes. I'll click here, Edit colors, click here and I'll set the following yellow color. Let's say, Okay, click Apply and then Okay, we have updated the color. In this way, we can create a map. I told you that you can use control plus mouse to increase or decrease, but you can obviously use this plus to get complete details and minus two zoom out. Okay, plus two zoom in, minus two Zoom out. That's it. So, guys, we successfully created a map chart in Tableau. It provided a clear geographical view of sales performance across the US. It also helps in identifying high performing regions, that is the darker shades and low performing regions, that is the lighter shades. That can be crucial for business decisions. So the map chart is very effective for spatial analysis and can be used to quickly identify trends and patterns across different regions. So, guys, we saw how we can create a map chart in W. Thank you for watching the video. 12. Create a Tree Map in Tableau: In this lesson, we will create a treemap in Tableau. First, we will understand what is a tree map. Then we will create a treemap to display the profit data segmented by different shipping modes. So let's see so a tree map displays hierarchical data as a set of nested rectangles. In the image, you can see the rectangles, and the darker color rectangle displays more profit, and the lighter one will display the lesser profits. Okay. Also, you can see we have represented a category or subcategory for each rectangle. And the size is proportional to the value it represents. In this case, we are using ship modes, standard class, second class, first class, or same day delivery. So here, the profits are more for standard class shipping mode. Okay. Let us also see another example. Let's say we want to visualize the sales data of ecommerce company categorized by product type and region. So we have product types and region. There are four regions north south east west and product types are electronics, fashion, and home goods. So what would your nested rectangles display? It will display the product types. So the largest rectangle will represent the product types. The smaller rectangles within each product type will represent the regions. Also, the size of each rectangle would be proportional to the sales value for that product type and region. Like we saw here, okay, the maximum profit was for the standard class. Therefore the size of the standard class, is more than the other shipping modes, and the color is also darker because the profits are more. Now, guys, let us see an example in Tableau. Okay, here's a Tableau. Let us create a new sheet. I'll double click and mention Treemap. Okay. We already saved the Tableau workbook as Amit underscore Tableau underscore visual. Okay. And we imported our sample superstore data provided by tableau only. Now, let us create a Treemap to visualize the profit data segmented by different shipping modes. Each section size will represent the total profit for that shipping mode. For that, we need to drag some dimensions and measures. Okay, so I'll just drag it. Here you can also see that when you click the drop down, some details are visible. If you want to check the details, let's say, of a field click describe, and here it's visible. I will have four values we also saw in the example that the shipping mode will also have same day ship mode, second class, standard class and first class. Okay. I'll click Cross. Now I'll just drag the ship mode or we can also first drag the measure. I'll drag the profit to the size under the marks. And then I'll drag the profit to the color pane. So this is your sum of profits. Okay, now drag your ship mode to the label pin. Now, here is your treemap. I already told you that the darker one will have more profit and the size is also bigger than others. The lighter one is same day shipping mode and its profit is also less. You can also change the view. I think standard was fine for us. Okay, you can also change the color by clicking here, dit colors. Just click here. Let's say, I'll change the color to the following. Click Okay. Apply. We have changed the color, and these are the dimensions and measures we dragged. Okay. In this way, we can create a Treemap. Let us see the tool tape, keep the mouse cursor, and the tool tape displays the ship mode as well as the profit, which is the highest for the standard class. So this tree map provided a clear and immediate understanding of how profits are distributed across different shipping modes. It allows for quick comparison and analysis, making it easier to identify which shipping modes are more profitable. So, guys, we saw how to create a treemap. The color is different now. We added a yellow color, darker one with maximum profit, and the lesser one with the least profit. Save it. Thank you for watching the video. 13. Create a Scatter Plot in Tableau: In this lesson, we will create a scatter plot in Tableau. First, we will understand what is a scatter plot. We will also see an example, and then we will see an example in tabu. Let us start. So a scatter plot, you can also consider it as a scattered plot or a scattered diagram is used to display the relationship between two continuous variables as a collection of points on a grade. So you can see the image here. Here, some points are visible. Each point represents a data point or an observation. The X coordinate corresponds to one variable and its Y coordinate corresponds to the other variable. When you keep the mouse cursor, you'll be able to see the tool tape as for subcategory. That is, we will visualize the relationship between sales and profit for different subcategories of products. Profit and sales are also visible, right? Let us also see another example. Let's say you want to get the relationship between the time spent in studying with the result. That is exam scores in percentage. So our X axis will have study time, Y axis with the exam score, and the data points will represent individual students study time and exam scores, like we have plotted in this image also. Now let us see another example and create a scattered plot in Table. So this was a tableau. Okay, first, I'll double click here and create a new worksheet. Let's see, I'll name it scatter plot. Okay. And we saved it under Amith underscore Tableu Underscore Visual Tableu workbook. We imported the sample superstore provided by Tableau only. Now let us create a scatter plot. So we are displaying the relationship between sales and profit for different subcategories of products. RX Xs will represent the sales and Y xs will represent the profits. And what would be the data points that is each point on the scatter plot will correspond to a subcategory. For that, let us drag the fields. So I'll drag the sales to the columns shelf, the profit to the rows shelf. And subcategory to the label. Now, let's see what it will create. It created Scatterplot. When you click here show me, you can see scatter plot it selected on its own. And recommended hint was also visible zero or more dimensions, two to four measures. So we added two measures and one dimensions in it. I'll just click Entire View, and this looks perfect now. When you keep the mouse cuts around paper, let's say, the profit and sales are visible. Okay, so in this way, we can create a scatter plot. This represents and helps in identifying which subcategories are performing well in terms of both sales and profit. Okay, I also provides a clear visual comparison, making it easier to spot the trends. This scatter plot is particularly useful for understanding the correlation between sales and profit across different product subcategories. So, guys, we saw how to create a scatter plot in W. We visualized the relationship between sales and profit for different subcategories of products. Thank you for watching the video. 14. Create a Bubble Chart in Tableau: In this lesson, we will understand how to create a bubble chart in Tableau. First, we will see what is a bubble chart, and we will also work around some examples. After that, we will create a bubble chart in Tableau. Let's start. So consider bubble chart as a three D. That is a three dimensional data as a series of bubbles or circles on a two dimensional grade. Okay, so on the right, you can see an image. And it represents one variable on the exact six. Consider that. Another variable on the YXs. A third variable is for the bubble size. The bubble size may represent volume value or magnitude. Bubble color can represent your category or classification or even range. So that would be your fourth variable. So when you will create it on T, the things will be more clear. Let us see another example to understand bubble chat. Let's say you want to visualize the relationship between the price of a house, which is your X axis, the size, your YXs and the number of bedrooms in it as the bubble size. Okay, now our bubble chart will display bubbles of different sizes and positions. There will be larger bubbles and smaller bubbles. Like here we have larger circles and smaller circles. Large bubble will represent, let's say, a spacious and expensive house with many bedrooms and smaller one will have fewer bedrooms. So let us see an example related to our sample store. So that we can understand bubble chart in a better way. We will visualize sales data across different shipping modes in Tableau for our sample Superstore. Let's see. Here is our table. Okay, let us create a new worksheet double click. I'll name it bubble chart. You can also give us space here, but I'm just saving the space because I'll be having more charts here later on. Okay, now let us create our bubble chart. Each bubble will represent a different shipping mode. For that, I'll drag and drop the dimension and measures. First, go for the profit measure. Drag to the size. Now go for the ship mode dimension. Here it is. Drag it to the label. Then take the ship mode and drag it to the color. Now you can see it's not visible. A tree map is visible. We already saw what is a treemap. Go to Show Me. Here you need to click on the bubble one. Here it is for PAC bubble, try one or more dimensions and one or two measures. We already did that. When I click, it will create. Okay, entire view, the same. Okay, now it's visible. Now you can see for same days not visible because a circle is too small. For that, what you can do, right click here, click format. Now, go to book. It's nine. If you want to show it, let's set eight and press Enter. It's visible now. Okay. Now it's fine. Okay, I'll click Cross. Now you can see the major value not visible. Okay, so I'll just drag the sales into the label. Now the sales is also visible. It's not visible for this because the size is really less. I can again change it, let's say. I'll right click and click Format and under this, let's set five. Seven, it's visible. It also updated the rest of them, so not a problem. Now it's looking fine. You would be wondering how to change the measure color here for that first I'll click here and check the legends. So here, legends are visible. If you want to change the color palette, you can click here and edit colors. But what I'll do, I'll click Close here and I'll set the bubble chart with measure color first so that we can set the same color with different shades. For that, I'll drag the sales into the colors. Okay, now you can see the color is similar, but darker one is having more sales than the lighter one, and it's visible here what I just said. But we can also change the color completely. That is the bubble chart color for that, click on the color. Then after that, click on Edit Colors and change the color. Let's say, I'll again try to give it a different color. I'll click the following and click Okay. Apply and Okay. We have changed the color. We have updated the color. Okay, we also change the label font so that same day is visible and darker one will have maximum value that is sales and the lighter one will have lesser value. Okay, and the size of the circle, according to the bubble chart, for the maximum size of the circle will always be there because the size is more for a circle with more sales. And when you'll keep the cursor, you can see the profit as well as sales. Okay. So guys in this way, we saw the size of each bubble is proportional to the sales amount for that shipping mode. The bubble chart provides a clear visual comparison of sales across different shipping modes, making it easy to see which mode has the highest sales. Standard class has the largest bubble indicating it has the highest sales among the shipping modes. This bubble chart effectively highlights the differences in sales performance across the shipping modes. So I'll save it in the same project. So guys, we saw how we can create a bubble chart in Tableau. Thank you for watching the video. 15. Create a Gantt Chart in Tableau: In this lesson, we will see how we can create a gant chart in Tableau. First, we will understand what is a Gant chart, then we will see an example, and after that, we will create it under Tableau. Let us start. So consider Gang chart as a bar chart. Okay. Let's say you want to illustrate a project schedule, displaying the task, the timelines for completing a project with the dependencies also. So you can use it for project management, and GAD charts are mostly useful for project management so that you can track your progress, visualize the timeline of the project, plan your workloads, like I have shown on the right. This chart displays order overtime for subcategories. Each colored bar indicates an order. The length of the bar represents the duration or quantity of the order. So here a Gang chart in the image is visualizing order date over time. Let us see another example. Let's say you want to plan a campaign, a marketing campaign for a product launch, we'll include the following task week wise. Let's say for ten weeks. The first two weeks will be for the setup and content creation, social media setup. Next one for influencer Outreach and partnership, then for email marketing, paid advertising, like your metaads nowadays, then week nine will be for planning and event to launch the product, and the last one would be for post launch review and analysis. So you can do this with a Gan chart. So through the GAG chart, different horizontal bars will be displayed. That will show the task with the start and end dates and the dependencies. You can plan and schedule task, you can track the progress and also identify some roadblocks in it. With that, the resources will be allocated and the team members will be assigned a task just like a project management tool. So let us see an example and create a GAG chart with our sample superstore data. So let us open W. So here was a Tableau. We will create a new worksheet, double click, and I'll name it Gandchat. Okay, we can also add a space between it, but not a problem. Okay, so we already saved our worksheets in Amith underscore Tableau underscore visual project. Now let us create our Gang chart. We will visualize order date over time. Okay, we will represent the order dates and different subcategories. So let us create and drag the fields. First, let us go to the marks. Go to the marks and click on the drop down and select Gant bar. Drag the order date. Okay, drag the dimension order date to the columns shelf, and after that, drag the subcategory which is here, the subcategory dimension to the rows shelf. Now you can right click on order date and select exact date from here. So, guys, we successfully created our Gan chat. If you'll keep the mouse cursor, for each date, the data will be visible. But you need to again, click on the order date and click filter. Here it is on the top. Now select a range of dates from here. Let's say I'll select from this I can also change it. Okay, this looks fine. I'll click Apply and then okay. Now drag the dimension, ship mode to the color. Now the colors updated and the Gant chart updated according to the ship mode. These are the legends. You can see the color and you can check the modes from here. Now drag the quantity to the size in the marks. Keep the mouse cursor on any of them. And here you can see. Let's say for the binder subcategory, shape more standard class, order date is the following because we selected exact dates from here, if you remember, quantity is 25. So in this way, we can create a ganchat we have displayed order data over time. The columns represent the order date and rows represent the subcategories. Each colored bar indicates an order. So I'll just, let's say, click on envelopes here. That means the order date is tentieth Feb 2024, Ship mode is standard class. Subcategories envelopes, and the quantity was five. Okay, so this is how each colored bar indicates an order. The length of the bar represent the duration or quantity of the order. I'll just click here and click Entire view, and this looks fine. So, guys, this Gang chart helps visualize order patterns and quantities over time across different categories. So this Gang chart we created now is useful for understanding how orders are distributed over time and across different product categories. So, guys, we saw how to create a Gang chart in T. Thank you for watching the video. 16. Create a Crosstab Chart in Tableau: In this lesson, we will understand how to create a cross chart in Tableau. First, we will understand what is a cross tab chart. Then we will implement it in Tableau. Let us start consider it as a chart to analyze and visualize the relationship between two categorical variables. Like on the right, we have shown the profit distribution across different regions and segments over time. Okay, so crosstab chart is also known as a contingency table or cross tabulation. Consider it as a statistical tool. Okay, if you want to display the frequency distribution of two variables as a table, then use the crosstab chart. This frequency distribution will display how different categories of one variable relate to different categories of the other variable. So let us see another example to understand. We are analyzing the relationship between the level of education and the type of jobs. So level of education here can be high school, bachelor's or masters, even PhD and the type of job can be sales, marketing or a manager, like employees in a company. So we will be able to display the frequency distribution of employees across different education levels and job types using a cross type chart so that we can understand that which of the education levels are common among different job types and which of the job types are most common among employees with different education levels like your master's bachelor's or PhD. So now we will create a cross tab chart in with a sample superstore data to display the percentage of profit across different regions and segments. Let's see. So here's our Tab. Let us create a new sheet. I'll click here and rename it to crosstab. So we already have our Tableau project, Amit Undersce Tableau Underscoe visual. Now let us create a cross step chart. We will represent the order dates by her on our column shelf and different regions on our rose shelf. We will also set the segments under the rose. We will get the profit for each segment in each region. First we will drag the order date dimension to the columns. Then the region dimension to the rows and the segment dimension to the rows. Then we will go to the measure profit and drag it to the text under the marks. Okay, here it is. I'll set the view to entire view. So now what is visible. We have the rows here to display the profit figures for each region here wise. You can see the profit figures for each region with the segment. Now let us set the percentage total of profit in each row, how we can do that. For that right click on the sum here, add table calculation. Under the calculation type mentioned, percent of total, keep it as it is, table across. Now, that's it. Click Cross. Now you can see the percent of total profit is visible. That is the cross type chart is created with profit percentage values. Okay, a small symbol is also visible on the right of sum profit that shows calculation. When you keep the mouse cursor, it will be visible table calculation. Keep the mouse cursor on any of the record. Let's say the following region east segment consumer of order date 2021 and percentage of total profit 28. Okay. So in this way, guys, we can create a Crosstep chart. You can also set it to standard to make it look like this. We'll save it. So, guys, we saw how we can create a cross tab chart in. So this cross tab chart provides a detailed breakdown of profit distribution across different regions and segments over time. It allows for easy comparison of profit percentages across different categories and years. This type of visual is particularly useful for detailed analysis and comparing data across multiple dimensions. Okay. Thank you for watching the video. 17. Create a Waterfall Chart in Tableau: In this lesson, we will create a waterfall chart in Tableau. First, we will understand what is a waterfall chart. Then we will see an example, and after that, we will implement a waterfall chart in Tableau. Let's start. So a waterfall chart is a chart through which you can easily display how an initial value affected by a series of positive or negative values. So in this case, in the right image, you can see running sum of profit based on subcategories. So you can display the cumulative effect of multiple factors on a single metric that is helping to identify the most significant contributors to the final result. So let us see an example to understand let's say you want to display the changes in a person's bank account balance over a month. So let's say the initial value is $1,000. The positive values can be obviously the paycheck, the salary, then the interest, and the negative values, what it can be, entertainment, utilities, rent, and others. Okay. So these are the negative values. So in this case, what the waterfall chart will display? It will display a series of bars, each representing a transaction, right? Then the bars would be stagged on top of each other to display the account balance. That is the cumulative effect on the account balance. And the ending balance will be visible obviously in the final so a waterfall chart will help you in displaying different transaction in understanding that how transactions affect the account balance, if it's positive or negative. It will also allow you to identify where your expenses are so that you can reduce it. So you will now have a chart displaying this so that you can evaluate it properly to reduce your expenses and plan your finances easily. Okay. Now, let us see an example based on our sample superstore data. We will display the running sum of profit for different subcategories of products. Let's see. So this was a tabu. I'll create a new worksheet, double click, and I'll name it Waterfall chart. Currently we have all these worksheets in our amid underscore Tableu Underscore visual Tableau workbook, we added our sample superstore data. Okay, if you want to list all the charts, you can click here like this. You can list all of them to the next one you want to go to the previous one, you can go from here. And here you can list it completely. I'll click here and I'm back. Now let us create our waterfall chart. For the X axis, we will drag our dimensions and measures. I'll go to the dimensions and I'll drag the subcategory dimension to the columns shelf and the profit measure to the rose shelf. Okay, so it created a bar chart. Right click on the profit. Here it is, click Create. Click calculated field. Now let's mention this for the calculation. And here also under the calculation, now the calculation is valid. So for each bar, we are representing the incremental profit contribution of each subcategory, showing how each contributes to the overall profit. Now, click Okay. You will be having a new field here now, drag it to the size shelf here under the marks. Right click here. Sum of profit, click on Quick Table calculation and select running total. The appearance of the chart changed, go to the mark spin and under this, select the Gant bar. And here is your waterfall chart. The symbol is also visible here because we added a calculation under sum of profit. So this is our sum of profit. Here and we added subcategories to the X axis, and to the Y axis, we added the running sum of profit, ranging from zero k to 300 k. Okay. This waterfall chart effectively visualizes the cumulative effect of sequentially introduced positive or negative values, making it easier to see how each subcategory contributes to the total profit. It also helps in identifying which subcategories are driving profit growth and which might be reducing it. Waterfall chart is useful for understanding the step by step accumulation of profits across different product categories. We added this calculation here, if you remember, minus profit, I'll right click and click Edit, so we added this code if you remember. So this was to invert the values of the profit measure. This is useful in creating a waterfall chart because it helps in visualizing both positive and negative contributions to the total profit. This is your negative profit calculation that inverts the profit values. This displays the negative contributions. So in this way, guys, we can create a waterfall chart. Thank you for watching the video. 18. Create an Area Chart in Tableau: In this lesson, we will create an area chart in T. First, we will understand what is an area chart, then we will see an example, and after that, we will create an area chart. So let us start as the name suggests, it is used to display the trend of a quantitative value over time. Let's say you want to get how different subcategories contribute to overall profit over time, you can achieve this by creating an area chart. This will also help in identifying trends and patterns in the data. Okay, so you can compare the contribution of different categories to a whole. So the right image displays the it visualizes the sum of profit over the years. The chart is broken down by different subcategories of products. Okay, each represented by a different colored area. So you can see different colors. It represents each subcategory. Area chart consists of an horizontal axis representing times here we are representing order date and a vertical axis representing the quantitative value, that means the profit as in the image. So profit is a quantitative value in data analysis. You can see the colored lines, the colored areas represent the cumulative values. So before moving further, let's see, another example, let's say we want to visualize the monthly sales of a company over a year. So your horizontal axis will have month because it includes your date. Vertical axis will have a quantitative value, that is sales so your area chart will display sales trend over the year. Okay, a line will be displayed. Colored areas will represent the cumulative sales for each month and the height of the colored areas will represent the sales value for each month, so that you can get the overall sales trend over the year. This will also help you in understanding the cumulative sales over time, as well as the months with the highest and lowest sales. So let us see an example of area chart in Tableau. So we will use our sample superstore data so that we can get the sum of profit over the years 2021 to 2024 with our area chart. Let's see. So this was our Tableau. Let us create a new worksheet, click and I'll name it. Area chart. Okay, I can also add a space or keep it as it is. Now let us create it. First, what I'll do? I'll drag the order date to the columns shelf. Then I'll drag the profit measure to the rose shelf. Okay. Now you can see a line chart is visible. So I'll just go to show me and click on Aachat. The following is our area chart. You can see in the bottom area charts. I'll click and it created her area chart. Okay, now we will drag the subcategory to color in the mark spin to apply the color and differentiate. Okay. Here it is. Subcategory to color. Now, here it is, guys, we have created our area chart. Okay, I'll just click here. Now, the legends are also visible to display each category. Okay, so what we did guys, we have represented the year of the ordit date as X xs and YXs represents the quantitative value that is profit. And the chart is broken down by different subcategories of products. That means the following subcategories, each represented by a different colored area, right and you can also change the colors. If you want, you can click here and click Edit Colors to change it, the color palette. So what does this trend represent? This displays how the profit for each subcategory has changed over the years. Okay, with a journal upward trend in total profit. So you can check, let's say for the accessories category. In 2021, the profit was 6403. In 2022, it's ten K. In 2023, it's nine K, and in 24, it's 15. Okay, so this is what is represented by our area chart. It displays how different subcategories contribute to overall profit overtime. It also helps identify trends in the data, such as which subcategories are driving profit growth. The area chart is particularly effective for understanding the cumulative profit contributions of various subcategories over multiple areas. So this is how you can create an area chart in T. Thank you for watching the video. 19. Create a Heat Map in Tableau: This lesson, we will learn how to create a heat map in Tableau. First, we will understand what is a heat map. Then we will see an example. And after that, we will implement heat map in Tableau. Let's see. So consider heat map as a map to display the relationship between two categorical variables using a two dimensional representation. For example, you can visualize profit and sales data across different regions and subcategories. You can display the density or frequency of data points within a matrix. You can also identify areas of high density a heat map consists of a matrix with rows and columns representing the two categorical variables. The cells within the matrix will have different colors according to the frequency or density of data points. A color legend will also be displayed obviously to interpret the colors used in the heat map. So whatever I discuss here, you can relate this with the following figure. We have displayed a heat map that identifies trends and areas of high or low performance by highlighting which regions and subcategories are performing better or worse on the right, sum of sales is visible. The darker one is having higher sales and the lighter color means less sales. And as written here, each cell within the matrix are colored according to the frequency or density of data points. With that, the matrix is having rows and columns representing the two categorical variables. So this visualizes profit and sales data across different regions and subcategories. Region, you can see Central East southwest and subcategories are also visible, accessories appliances, art, binders, and others. The color intensity represents the magnitude of profit above and the magnitude of sales performances across different regions and subcategories. Now, let us see another example. Suppose, let's say we want to visualize the usage patterns of a mobile app. It will display the frequency of user interactions across different screens and features on a heat map. So a heat map will display a matrix like I've shown in the previous example. The matrix will have app screens on one axis and features on the other. The cells were also colored in the previous example, remember? So here the cells will be colored according to the frequency of user interactions. That means a darker color will indicate higher usage and the lighter color will display lower usage. Also, the color legend was visible to display about this darker and lighter color. A color legend is also displayed to interpret the colors. So using this heat map, we displayed the most frequently used screens and features so that we can understand how users navigate through the app. So this will also enhance user experience and engagement and informed design decisions. Like in the previous example, we saw profit and sales for a particular reason for a particular subcategory. Now let us implement heat map on T, so we will evaluate on the basis of our sample superstore data so this was our tabu. Let us create a new worksheet, click and select, write the name heatmap. Okay, here it is. Now let us create our heat map. First, what I'll do. I'll select the dimension subcategory and the measure profit. So for multiple selections, click on the first one, press Control, and then click Profit. Okay, now we've selected both. Now, keep the control as it is and go to ShowMe after that, click on the heatmap. Here it is. Okay, it's written. Hint is visible, one or more dimensions or one or two measures. Click here and your heat map will be visible. Now drag the measure sales into the color under the marks shelf. Now region because we also want the region to be displayed for all the sales. That means sales by region. So I'll just drag region to the column shelf. Here it is. Now heat map is visible. We have displayed the visual of the sales and profit across different regions. Okay, I'll click this. The size of each square box is according to the higher and lower profits. These values likely represent different profit levels. The lighter color means less cells and the darker color means more cells. I'll change the view to entire view, and it looks great now. If you'll keep the mouse cursor on any of the cell, let's say, I'll go for the chairs here. The details for the region as well as a profit and sales for cheers category is visible. Darker one, so the sales are higher. If you click on the lighter one, you can see the sales are less in comparison with the following. Okay. That is for the art subcategory I'm showing. So in this way, we can create a heat map. This heat map allow us to create a quick visual comparison of profit and sales performance across different regions and subcategories. It also helps identify trends and areas of high or low performance by highlighting which regions and subcategories are performing better or worse. So we saw how a heat map can be useful for understanding the distribution and intensity of data across multiple dimensions, making it easy to spot the patterns. So, guys, we saw how to create a heat map. Thank you for watching the video. 20. Create a Histogram in Tableau: In this lesson, we will create a histogram in tableau. First, we will understand what is a histogram. We will also see an example, and after that, we will create a histogram in tableau. So let's see if you want to display the distribution of a continuous variable by grouping the data into discrete intervals called bins, you can use a histogram. Also display the frequency or density of data points within each bin. Now, you would be wondering what is a bin. Okay. So consider a bin in histogram as a range of values that is used to group a set of continuous data points. Each bin represents an interval of the data, and the histogram shows the frequency of data points that fall within each interval. Consider a bin as a bucket. Okay. Each bin covers a specific range of values. Let's say you are creating a histogram of test scores. So one bin might cover scores 70-79, another 80-89 and so on. Another example, we can see that exam scores class for some students. Let's say a bin is created with a width of ten points. So you'll be having bins like zero to nine, ten to 19, 20 to 29, 30 to 39, and so on. So you would be wondering histograms with bins are useful or not. Yes, it's obviously useful for understanding the distribution of data and to identify patterns. Also help in comparing the distribution of different datasets. As you can see in the right image, we have a stagged histogram here, and the legends are visible on the right so that you can identify the colors. The bin is also visible in the bottom and the count of quantities on the left. So one of the values are visible, that is the tool tip for the bin as two, the count of quantity has around 1121, that is one K and the region is central. Central on the right, you can see the color and match it. The topmost value, I should say, in the stacked bar is 1121 and the same we are displaying. Let's say another example, we want to display the distribution of daily rainfall in the city over a year. So obviously, we will create some bins for it for the range. Here we have bins of 1 millimeter ranges, that is 021, one, two, 223. Our histogram will display a series of bars, each representing a bin. The X axis will represent the rainfall ranges and the Y will represent the number of days. Also, the height of each bar will represent the number of days with rainfall within that bin that is within that range. This histogram visual will obviously help in understanding the pattern of rainfall so that we can identify the most common rainfall ranges. This will later on help in managing water also in controlling the floods. So this is really important. Now let us create a histogram in Tableau with our sample superstore data. So we will display the distribution of the variable quantity across different regions. So, guys, this is our Tableau. I'll click here, New worksheet, and I'll rename it histogram. Now we will create a histogram. In our Amtnderscoe Tableu Underscore Visual project that we already created, drag the measure quantity to the rose shelf. Go to ShowMe and go to Histogram, click on it, and on clicking, it will automatically add a column for you and create a histogram. Click here again, and now you have your histogram. The CNT is for the count here. Can you see here, CNT? The bins are ten here. A bin is short for binomial. It is a range of values that is used to group data points. It is also known as intervals or classes. I already discussed before what is a bin? The quantity is displayed with values ranging 0-4875 and divided into ten bins. Okay, on keeping the cursor, the tool tip is also visible. Now let us create a staged histogram, drag the dimension region to the color. So what will happen after that, I just dragged it and now you have a stack distogram with four legends displaying the following color for central and in the top, you can see the region is central. So you can relate this with your legend. Okay, the count of quantity is also visible. The stack represents the values of the dimension region. If you want to display the count quantity of each region as a label, you need to press control and then drag the CNT quantity from the rows to the label. So that it's also visible. Now your count of quantity is visible on your staged histogram, when you'll keep the mouse cursor, it's visible. So in this way, guys, we can create a histogram, our X axis represented our bind quantity values, the YXs represents the count of quantities within each bin. The regions are central east south and west and represented by colors. Each bar is stagged by region. With each color representing a different region. For the bin with a quantity of two, let's say, the central region has a count of one, one, two, one. So this histogram provides a clear visual representation of the distribution of quantities across different regions. It helps in understanding which regions have higher or lower counts in specific quantity bins, allowing for a quick comparison. Histogram is particularly useful for analysing the frequency distribution of data. And identifying patterns across different segments. So, guys, we saw how we can create a histogram in tabu. So right now, we have all these graphs. We have created over ten graphs and charts. If you want to see all of them, click here or click here. So we created around 13 charts and graphs. If you want to reach here again, click here and you are back. So guys, we saw how to create a histogram in tableau. Thank you for watching the video. 21. Tableau - Filters and their types: In this lesson, we will understand what are filters in T. With that, we will also understand its purpose as well as its types. We will also implement filters. So let us start. Consider filters as a crucial component in allowing you to narrow down your data to specific subsets, making it easier to analyze and visualize. So you can select specific data points, or if you want to include or exclude a dimension or a measure from a view, you can do it with filter. Easily narrow down or consider refining your data with filters by applying filters, highlight the key insights from the data. With that, you can also focus on trends reduce the complexity of data. With filters, you can explore different scenarios by creating interactive dashboards. Now let us see the types of filters. So the top three types of filters are measures and dates filter. Dimensions filter, you can easily understand that it is based on the categorical values with that measures are based on numerical values like your sales and profit, and the dates will filter specific periods. With that, some more types of filters are also there. That means quick filters, context filters, conditional, top, as well as wildcard filters. So in the next lesson, we'll be focusing on the first type that is filter dimensions. Then one by one, we'll be covering all the types of filters with examples. So let us start with filter dimensions in. 22. Tableau - Filter Dimensions: In this lesson, we will understand what are filter dimensions in T. So this is one of the types of filters in tab. We will also see an example by implementing filter dimensions on Tab. Data start. So as the name suggests, filter dimensions means you can filter by categorical values like state, regions, products category. Okay, so the filters that are applied on dimensions in T are known as filter dimensions. So we saw the working of Tab. On the left, we have dimensions and measures. On the top, we have dimensions and in the bottom, we have measures. So your dimensions include your category, subcategory, region, product. Okay. So measures include sum of profit, sum of sales. That means your dimensions are qualitative and measures are quantitative. So here we are discussing about filter dimensions. Now we will see an example. And implement filters on tabu. We will apply the dimension filters on the subcategory of the products in our sample superstore data. First, we will create a new Tableau workbook that is a new project and give it a name Amed Underscore Tabu UnderscoeFlters. Within that, we will create our first sheet and name it as filter dimensions. So let us start. So, guys, this was our previous workbook. Let us create a new workbook for filters, God file, click New. So our new workbook is visible. Okay, I'll close the previous one. So this is our workbook. We will first save it as Amith underscore Tableau Underscore filters. Click Save. Now we have saved it. Now let us connect to the data. Directly click here, Connect to data, and we have the same screen. You can directly click here Sample Superstore or I'll click on Microsoft Excel, and it will take me to the same sample data under the MTableRpository, we have discussed the same before also. Click this and click Open. Now our sample superstore is visible. We need to drag the tables. I'll drag orders. Ive data, fine, orders sheet is visible. I hope you remember all the sheets are listed here. We are using the order sheet. Now I'll click on Sheet one, and I'll double click and rename it. I'll name it filter dimensions. So now we will filter the dimensions. First, I'll go to dimensions. So first, I'll drag the ship mode to the shelf, then the subcategory to the rose shelf. After that, for the measure, I'll go for sum of profit. Drag it to the columns. That's it. Now I'll drag the subcategory to the filter spin. So this is the filter spin for a filter, so I'll just drag it Now, all our subcategories are visible and we will apply the filter here only. The filter dialog box is visible. First, select none because you want to unselect all of them. Okay. This will deselect all. Okay, here it's written selected zero of 17 values. Now click Exclude so here we are excluding the categories. So we have excluded none of them. Whichever I'll select here will get excluded. Let's say I'll exclude appliances, chairs, copiers and furnishings. We have excluded four of them, and it's visible excluded four of 17 values. Now when I click Apply, currently, all the values are visible. Here you can check. All the subcategories are visible. After clicking Apply, what will happen? These four will exclude from the result. Apply, Okay. Now you can see the same bar chart is visible and all the subcategories are visible, excluding those four subcategories for which we applied the filter. That means appliances, chairs, copiers and furnishings are not visible. Rest all are displayed for the ship mode. Okay. And when you'll keep the cursor, you can get the details about the specific subcategory with its profit and ship mode, excluding all those four subcategories. So guys, we applied filter on one of the dimensions that is subcategory so this is how we can exclude using filters. We have successfully applied filters on dimensions and saved it as the filter dimensions sheet in the AMT Tableau Underscore filters workbook. Thank you for watching the video. 23. Tableau - Filter Measures: In this lesson, we will understand what are filter measures in Tableau and how we can implement it. We will understand how filters can be applied on measures with an example that will be implemented on Tableau itself. Let's start. So filter measures, as the name suggests, is used to filter measures in Tableau. So whenever you load your data on the left, you can see the bifurcations of dimensions and measures we already saw in the previous lectures, Okay, so such kind of filters can only be applied on measure fields like we have sum of sales and sum of profits in our sample store data. So now let us implement it on Tableu and filter measures. We will create a new sheet and name it filter measures within the same Tableau workbook, that is the same project Amtnderscoe Tableu underscore filters dot TWV. So let us see. So this is our tabu. Let us create a new worksheet, click and I'll name it filter. Measures. Now we will see the example and this sheet is also in our mid underscore Tableu Underscore filters project. That is Tableu workbook. Now let us filter measures. First, I'll drag the subcategory dimension. So if you want to again check which are the dimensions and measures, just try to drag it and you can see the bifurcations on the lift. The above one are dimensions and the below one are measures. Okay. Now I'll just drag subcategory two rows and sum of profit two columns. Okay, now we have our bar chart. First, I'll change sum of profit to average. For that, click here. Okay, under measure sum, change it to average. Okay, now we have the average profit. And also the columns, it's visible, average profit instead of s profit. So we have successfully changed it, aggregated it. Now we will drag the measure profit to the filter like we previously did in dimensions. For the dimension you want to filter, you just need to drag it here. Similarly, we are implementing a filter on a measure profit, so I'll drag and take it to the filter's shelf. Now the dialogue box is visible. Select average within this. Okay, how do you want to filter on profit by average? Then click next Here, choose at least and give a value to filter the rose. Now I'll give it, let's say, 15. Okay, at least 15 now. And I'll click Okay. Now, guys, what is visible? Only the subcategories with average profit above 15 are visible. Okay, because we have applied the 15 filter before, at least 15. You can also check it. It's 54.1 in accessories. I think this is very less. Still, it's above 15 because we applied a filter 15.1, rest 24.98 01.3. So through this, we can easily filter measures. And keep the mouse cursor to get all the details. All these subcategories are having average profit above 15. I'll save it. So, guys, we saw how we can implement filter son measures. Thank you for watching the video. 24. Tableau - Filter Dates: In this lesson, we will understand how to filter dates in T. With that, we will also understand the concept and implement an example on Tableau itself. So let us start. So filtering dates refer to filtering according to specific date ranges or periods. So just like we did in the previous lectures to filter dimensions and measures, we will drag any of the date fields to the filters shelf or pan so that you can filter by dates. It also helps you in analyzing specific time periods, trends and seasonal patterns more effectively, like selecting relative dates, selecting time frame. Okay, so we will see an example. We already created the Amit underscore Tableau Underscore filters workbook, and within that, we will create a new sheet, filter dates, and filter the dates accordingly. So this is our Tableau. First, I'll create a new sheet by clicking here. I'll name it filter dates. Okay. And we already saved this in our amid underscore Tableu Underscore filters workbook. Now let us filter the dates. Now, first, I'll drag the measure profit. This is the measure, if you remember, if you'll drag it and you can see the difference. Drag profit, drag the profit measure two. Rose. Now it's visible sum of profit and after that, drag the order date. That means the following to the columns. Okay, now a line chart is visible, but we need to filter by dates. Here, you can see order dates are visible. Now drag the order date to the filters so that we can filter by date. Now what is visible, a new dialog box is visible. Okay. Click here, range of dates and click Next. Now the section is visible. Here select range of dates already selected on its own. And here set the date trans to get the profit between a specific period because we have already selected sum of profit for rose, so I'll select a date. You can also mention the date from here like this, or you can just drag it. So I'll just drag it. Okay, this looks fine to me. And the last, you can also drag it like this, but I'll keep it here. This looks fine. Okay. Now what you need to do, it's very easy. Click on Apply then Okay, because we have already selected the range of dates. Apply and o from second October to 25th, December. Now what is visible? The filtered values are visible. We are filtered by dates and the profit is visible. For the same time period which we mentioned, I'll just change the view to entire view. This looks fine now. For 2023 and 2020 for the same time period, which we mentioned in the filter. Okay, if you want to check again, click here, Edit filter, and this was the range. Okay, from second October till 25th December. Okay. So in this way, guys, we can filter by dates. We can now see the filtered values based on a specific date range filter, and we save the sheet as filtered dates under the same project. Thank you for watching the video. 25. Tableau - Quick Filters: In this lesson, we will understand what are quick filters in Tableau. So we already discussed the three types of filters that is dimension, measure, and date filters. Now we will see some more types of filters. One of them is quick filter. We will understand what are quick filters. With that, we will also see an example on Tableau itself. Let us start. The most common filters are quick filters because they are easily available. So we will see an example regarding the same quick filters. Such filters includes the following methods. So let's say you only want to select one value at a time, you can use a single value. Okay. With that, you have your single value as a drop down list, single value as a slider, so it makes your work easier to filter. You also have the same options for multiple values. That is selecting one or more values from a list, dropdown or a custom list. With that, you can also work around the Wildcard match in filter. That is selecting values containing specific characters. Let's say want only the subcategories with names starting with A or with name ending with K, so we can achieve all these using the quick filters in Tableau. Now let us see an example of one of these filters, and we will create a new sheet, quick filters in the same Amith underscore Tableau underscore filters in which we already saw some types of filters. Let us start with the example. So this was a tableau. Let me create a new worksheet by clicking here. Double click and rename. Quick filters. Okay. So we already implemented filter dimensions, measures, and dates in this same workbook mid underscoe Tableu UnderscoeFlters. So now we have our quick filters sheet. Okay. Now let us drag the subcategory. Here it is two rows and profit that is sum of profit two columns. Now we have our bar chart. Horizontal bar chart is visible. Now, right click subcategory and click Show Filter. Now the subcategories are visible. Okay, you can de select any of them, but a dropdown is also visible here or you can directly click on the search to find the values. Okay, what I'll do, I'll just click on the dropdown. And all the quick filters are visible, which we already discussed in the PPT. You can see single value, single value dropdown, slider, multiple values, list drop down, custom list, and wildcard match. So these are the quick filters, commonly visible, easily accessible, right? So let's say I'll go for the wildcard match. We will filter the subcategories of the bar chart. By default multiple values by list is selected. Click on the Wildcard match. Now you have the search box to apply the Wildcard filter. Now, let's say we want subcategories that begin with the letter C. I'll just type C star and press Enter. So this expression we typed to get the subcategories that starts with the name C. Now what is visible, guys? Only the subcategories that begins with the name C can be seen. I'll just go for the entire view. No. Only the subcategories that begins with C is visible. You can keep the mouse cursor and get more information. I'll just switch it to standard again. This looks fine to me. So in this way, we can apply quick filters. I have shown one of the examples, only the subcategories that start with the latest C filtered out like this. I'll go to file and click Save. So, guys, we saw how we can apply the most common quick filters in T. Thank you for watching the video. 26. Tableau - Context Filters: In this lesson, we will understand what are context filters in tabu. With that, we will also understand its purpose and how we can implement context filters on Tabu. Let us see so context filters are a powerful feature in Tableau that allow you to filter your data based on the context of your visual. Okay. That means you can apply the filter to a specific worksheet or visual rather than the entire workbook. So it is like a temporary filter. It also helps in enhancing the performance by reducing the amount of data that needs to be queried. So Tableau will aggregate that data at the level of detail of the view when you apply Context filter, and it is temporary and only applies while the filter is being created or updated. So it won't apply to the entire workbook. You need to remember that context filters are applied after dimension filters and before major filters. It can also be used to analyze data for a specific product or product categories. Okay. Now let us see an example to create a context filter. You just need to drag a dimension to the filter shelf, right click and select Add to Context. So now we will see an example on Tab and a new sheet will get created with the name Context filters in the same matenerscore Tu Underscore, filters dot TW Tableu workbook. So let us see the example. So this is our tabu. I'll create a new worksheet, click, and I'll just rename it. Context filters. Okay. Now let us implement. We have saved all our filter examples in the Amith underscore Tableu Underscore Filters workbook. I'll drag the dimension subcategory to the rose shelf. Drag the measure sales to the columns, shelf, no bar chart is visible. Okay, what we are doing here, we will find a top five subcategory of products for the category called Office Supplies using the Context filter. Now our bar chart is visible displaying the sum of sales with subcategories. Drag the subcategory to the filter spin. We will take a dimension now and add it to filters, just like we did in the previous lectures for filtering dimensions, measures, and dates. Now let us drag the subcategory dimension to filters. Go to the top tab. Here it is. Click the dropdown and select the option by field. Let's say I'll set the top ten to top five because I want a top five fields, and I'll keep the rest as same. By sales and some. Okay. Now I'll click Apply then Okay. Now what is visible? Top five subcategories. By sales, some are visible, and the Brchard also updated. Now we will drag the dimension category to the filter spin. And the filter is visible. That is a new filter dialogue box is visible. Three categories are visible. Okay. These are the categories we have. We want the top five subcategory of products for office supplies. So what I'll do, I'll just select office supplies. And click Apply and then Okay. It will show two subcategories of our category office supplies. That means binders and storage, with the sum of sales and the filter span or shelf is also showing us category office supplies because we have filtered it. Now we will add the context. Right, click the category Office Supplies, and you can see add to context, click on it after clicking. Now the subcategory of products from the category office supplies, which is among the top five subcategories across all the products is visible. You can also get more info by keeping the mouse cursor so that the tool tip is visible. So in this way, guys, we applied the context filter to display the subcategory of products from the category office supplies. That is among the top five subcategories across all the products. Okay, because we also selected top five, if you remember, while creating a filter for subcategory, I'll save it. So, guys, thank you for watching the video. 27. Tableau - Conditional Filters: In this lesson, we will understand what are conditional filters in Tab. With that, we will also seeing an example and implement on Tab. Let us see. So conditional filters allow you to filter the data based on conditions, narrow down your data to specific subsets that meet certain conditions with the conditional filters. So this feature enables you to create more dynamic and flexible visuals. So you can filter your data based on specific conditions or criteria, and this will allow you to create more dynamic and flexible visuals. Now, let us see the operators under conditional filters equals not equals. If you want to filter data where the value equals a specific value, then use the equals operator. Similarly, we have other operators also like not equals the opposite of the equals, greater than means greater than a specific value. Less than means less than a specific value between means range. I not in means where the value is present or not present in a specific list. When we see the example, then the things will be more clear. Now let us see an example in the same workbook Amith underscore Tableau underscore filters. We will create a new sheet and name it conditional filters so that we can apply filters based on conditions. Let us see the example. So this is our Tableau, create a new worksheet click here, and I'll click to rename it. Okay, so name it condition or conditional filters. Okay. Now, what I'll do, I'll see an example to find the subcategory of products across all segments whose sales are above 50 K. For that, I'll drag the dimension segment to the columns. A After that, drag the measure sales to the columns shelf. After that, drag the dimension subcategory. That means the following to the rows shelf. Now our chart is visible. Drag the dimensions subcategory to the filter span. Here it is. Now a new window will be visible. Go to the condition tab for the condition filters. Click the dropdown. First, go to By field. Select By field. And within this, select the operator, we have discussed these operators just now. I'll select greater than equal to value, I'll set 50,000, 50. Okay. Rest key Azits sales and sum. Click Apply, then okay. Now the chart changed because we have set the condition filter. We will get a chart with only a subcategory of products that have the required number of sales. That is, now we have the subcategories with sum of sales above 50 K. We will save it. So, guys, we saw how we can apply conditional filters in T. Thank you for watching the video. 28. Tableau - Top Filter: In this lesson, we will understand what are tough filters in Tableau. With that, we will also see an example and implement it on Tableau. Let us see so if you want to filter data to display only the top and values based on a specific measure or dimension, then use the top filters. This feature enables you to focus on the key data points and simplify your visuals. So if you want to get the subcategory of products with top five or top ten sales, you can use the top filter. Now we will see an example and implement top filters on Tab. In the same Amith underscore tabu underscore filter, tabli workbook, we will create a new sheet to filter and create a filter. Let us see now here is a Tableau. I'll click on New Worksheet and double click to rename it. Let's say I'll add to filter or to filters. Okay. Now we will get the subcategory of products with top five or ten sales. Drag the measure sales to the columns shelf and the dimension subcategory to the rose shelf. Now a bar chart is visible. Right, click the subcategory and click filter. Now dialogue box will be visible. Go to the top for the top filter. Here, let's say we will click BiFeld keep it top only, and here you can add five, ten or any value. I'll go for five. Let's say to get the top five. Sales and some keep it as it is. And this also keep it top. This will give us the subcategory of products with top five sales. After clicking, apply, click Okay, and now the top five sales are visible. So this is the bar chart that displays a subcategory of products with top five sales. So these are subcategories only right. So in this way, guys, you can apply the top filter in tabu. I'll save it, and we have saved all the filter examples and worksheets under the score Tu Underscore filters workbook. Thank you for watching the video. 29. Tableau - Wildcard Filter: In this lesson, we will understand what are wildcard filters in T. With that, we will also implement it on T. Let us start. If you want to filter data based on substrings or patterns within a dimension, then use the Wildcard filters. Let's say you want to filter the categories or subcategories that contains a specific substring or starts with a specific letter or even ends with a specific letter, then the wildcard filters are of use. So I just discuss the types of wildcard filters. That means contains starts with, ends with a specific letter. It can also include matching the specified regular expression pattern. So we can filter our data using wildcard characters with the wildcard filters. This feature enables you to search for patterns or partial matches in your data. Since we are discussing about wildcard, so I hope you know the most commonly used wildcard characters, that is your asterix, kosher mark person sign. If you want to match any number of characters or even a single character, then you can use these wildcards. I hope you have also used it on your operating system. I generally use them on my OS to find PDF files. So I just type star Dot PDF to find all the PDF files on my system under the search box. Okay. So in this way, you can also implement this in T. One of the examples can be to find categories or subcategories with a specific substring or with a specific letter, beginning with a specific letter or ending with a specific letter. Now, let us see an example of wildcard filters. In the same Amith underscore Tableu Underscore filter Tabu workbook, we will create a new sheet and name it wildcard filters. So let us see the example. This is the tableau. I'll click here to create a new worksheet and double click to rename. Let us name it Wildcard filters or filter. Okay. Now, first, I'll drag the measure sales that is sum of sales to the columns. Shell then the subcategory to the rose shelf. Okay, now we have a bar chart. Let us apply filters. Right click the subcategory and click filter. Click the Wildcard tab. Here it is, and all the four options are visible, which we already saw in the PBT. Okay, we will get all the subcategories that begin with the word P. So select starts with under the text below, match value, write P. So all the subcategories with the letter P will be visible now, click Apply, then okay but before let us check, Okay, only paper and phones should be visible. Click apply, then Okay. Now you can see all the subcategories beginning with the letter P are now visible. So in this way, we can apply Wildcard filters in Tu I'll save it. You can also keep the mouse cursor to get the sales details of subcategories, starting with the letter P. Thank you for watching the video. 30. Groups in Tableau: In this lesson, we will understand what are groups in T. With that, we will also see the types of groups and implement an example of groups in T. Let us see Groups are a way to categorize dimensions based on specific criteria or conditions. There are two types of groups based on dimensions and measures. So the dimension groups include grouping dimensions based on specific values or ranges, and the major groups includes grouping measures based on specific values or ranges. With that, we can also combine groups together. So we will see an example to create groups in W and group specific fields. We will aggregate the value of let's say two categories together. We will create a new Tableu workbook, Am underscore Tableau Underscore groups, and within that, we will create a new sheet with the name groups. Let us see. This is our tabu. We created Amith underscore Tableau filters and implemented the filters. Now let us create a new workbook, go to File click New. Here is the new workbook, so I'll close the previous one. Maximize. Now I'll go to File and first save, click Save and I'll save it as Amith underscore T underscore groups. Okay. Extension is also visible dot TWB and the location of your workbook is the following in tabu. Click Save. Now let us connect to data. We will connect to the same sample store data provided by Tab. Click Connect to data. The same interface is visible. You can directly select Sample Superstore from here or you can click Microsoft Excel and select the same Excel provided by Tab under the MW repository folder. I'll click here, click Open. So we have loaded our data. We will drag the orders sheets from the sample superstore. Now, the orders sheet that is a table is visible. Okay, I'll create a new sheet by clicking here. I'll double click and rename groups. Okay. Now let us implement groups in W. On the left, we have dimensions and measures, drag any of them and check the difference. Can you see the dimensions and measures here? Okay. And this is our table orders and the following added. That is we connected the orders data source, Excel. To implement groups, we will drag the dimension category to the rows, shelf, and sum of sales to the column. Sum of sales is a measure, so it's below, sum of sales to the columns. Now what is visible? We are having three categories here, furniture, office supplies, and technology, and a bar chart is visible. We can also change the view from here, but I'll keep it standard. Now, right click on the category on the left under dimensions, and click Create then Group. Now the create group dialogue box is visible and your fields are visible, which were three. As we saw here, from here, you can group. Add the name of the field, use the Control key on the keyboard and select any two categories to group. From these three, we can group any of the two. I'll press the Control key and select, let's say, furniture and technology and now click the button group. Now what is the name furniture and technology, the group name. We can also change it. Click apply and then ok. And now on the left, you have your dimension with group. So this is the group. You can also see the sign here. This is the group of categories. That is two categories in our case. Now, you need to drag the following to the rows. You can click here and remove it now. Now your categories are visible, but furniture and technology is now grouped and their values are also grouped. You can go to Entire View and you can check furniture and technology sales values are also added because we grouped them. So guys, this is how we can create a group in T. You can go here and save it and the project name is Ahmed Underscoe Tableu UnderscoeGroups. Thank you for watching the video. 31. Joins in Tableau: In this lesson, we will understand what are joins in Tableau. With that, we will also see the types of joins and an example that will be implemented on Tableau itself. Let us start. So if you want to combine the data from multiple tables that is more than one table, then you need to use joins. So there are different types of joins that includes your inner join, left join, right join, as well as fol outojoin. So let us see what does it include? Let's say we are combining two tables. So it will return only the rows that have matching values in both the tables. With left join, as the name suggests, it will return all the rows from the left table. And the matching rows from the right table. You need to remember that if there is no matching values, then the result will contain null values. Then comes your right join. Right join is the opposite of left join. In this, the return value will be all the rows from the right table and the matching rows from the left table. And what about the full outojoin? It will return all the rows from both the tables. Also, null values will be returned in the columns where there are no matches. Let us see the figure. Now you can easily relate what I just said about left join, right, join, full outer join, and inner join. So in the left join, I said that it will return all the rows from the left table, so you can check the color also. It will return all the rows from the left table and the matching rows from the right table. So whatever is matching between left and right will also be a part of left join. Now comes the right join. Here first, consider the left circle as the left table and the right circle as the right table. Okay, so we are joining two tables. In the right join, as I said, it is the opposite of left join. It will return all the rows from the right table. And the matching rows from the left table. So you can also see the matching rows with the color. Then comes your inner join. Returns only the rows that have a match in both the tables. That's why the color value is what it will return. The match of both the tables, left and right. Full auto join, both the circles are colored, that means it will return all the rows from both the tables. So this is how you can differentiate between all the types. Now we will see an example to join the tables. We will create a new Tableau workbook and name it amid underscore Tableau Underscoe Joins. Within that, we will create a new sheet, and we will join two tables. Okay, so let's see. So this is our Tableau. First I'll go to file and click New. A new workbook is visible. I'll close the previous one. Okay, now this will be a workbook for joins. So I'll go to File and Save as. Let us name it Amith Tb underscore Joins. And I already told you that it will get saved in the following location under my Tb repository. Okay, click Save. Now we have our project. Let us connect the data, the same sample store data. Click Connect to data. Now here I can connect this directly, or I'll just click Microsoft Excel and select the sample provided by Tb. That is sample superstore dot Ecelx. Click Open now, here are the sheets available of the sample Superstore. Let us open it again. So this was our sample Superstore. I'll open. Now what we will do we have three sheets, orders, people and returns. That means three tables. So now we will join the orders and people. And after joining, it will automatically join using a common column. So let's see which one it will be. I will be your region. Okay, because region is here as well as here, o South east central, west and here we are also having the region. So it will join using the region column on its own. Now let us drag, I'll drag the orders table first. After dragging, now the table is visible orders. Okay. Now let us drag the people table. Now a line will be visible here. That means we are joining both of them. So this line is visible, that means we have joined it, and here is the join. Now, based on the column region, it's visible from orders and from the people. So it has automatically shown us. Okay, what we'll do since we have joined both of them, I'll click on Sheet one. I'll name it, let's say joins. Okay. On the left, we have a sample superstore and two tables. The fields of both the tables are visible orders and people. This was the region, and this was the region, which connected. Okay? Now we will get the regional managers for the states by joining both the tables. Now drag the state column here is the state from the first table orders and drag it to the Rose shelf. Then the regional manager from the people table, here it is, drag it to the Rose Self. Now the list of the regional managers are visible by joining Board tables. That is people and orders. So in this way, guys, we can implement joins. We joined board the tables. We have saved it under Amith Underscore Tableau Underscore Joins workbook. Thank you for watching the video. 32. Sorting in Tableau: In this lesson, we will understand how we can sort the data in tab. So we will understand what is sorting, how it helps. What are its benefits and use cases. With that, we will also understand the types of sorting in a way by creating an example and showing all the ways through which we can sort the data in tab. Let us start so sorting means to sort the data, that means to arrange the data in a specific order like arranging the data in ascending order or descending order. But in T, we have many other ways to sort the data. Okay? So we will understand them one by one. So sorting helps you in getting the trends in the data by sorting the values, and it obviously arranges and organizing the data that easily helps in understanding it. So let's say you have a table and in that you want to list the categories with the maximum sales, so you can use the descending order sort and arrange the categories from top to the bottom. That means the topmost subcategory will be having the maximum sales and the bottom will be having the lowest. So you can easily organize and analyze the data through this. Obviously, it will also enhance the effectiveness of the visuals you'll be creating such as bar chart, tables, Pie chart, Gan chat. Okay. Now, these are the benefits and use cases. The data analysis will get enhanced because you'll be having the true picture of your sales based on categories, subcategories, products. Okay. It will also save your time so that you don't need to analyze it accordingly. If you have a lot of subcategories, you can easily arrange. And whichever chart you'll be creating, whether it's a pie chart, bar chart, column chart, all of them can be easily created and enhanced so that it's easier for the team members to understand. It's use cases. Okay, so you can easily sort the customer data by demographics based on, let's say you want to get the sales for a particular state in a country. Based on your behavior and preferences, you can easily analyze the data of the customer. Get the sales trends based on the region product or period. That is the time period. Let's say you want for the top sales or profits in the year 2024 or 2025, you can easily get it by sorting and understanding it. You can also visualize the results, by sorting the survey data by the questions. So let us see the options. So whenever you load a new data in T, you'll be getting these four options initially. If you want to sort in alphabetical order from A to Z, that would be ascending from Z to A would be descending. If you want to apply the sort separately to each table, then use the A two z ascending per table. This will sort from A to Z. That is an ascending order. And the opposite of this will be the last one, a two z descending per table. That means in reverse alphabetical order from Z to A, applied separately to each table. So let us see some examples related to sorting in Tableau. We will first sort in ascending order then descending order. Then we will understand what is sorting the table data, what is sort by order, sort by field, and how to manually sort it. So let us begin. We will open Tableau and create a new Tableau workbook for these examples. So this is our Tableau. I'll go to file and click New for a new workbook. The new workbook is visible. Close the previous one. Now I'll save it, go to File Save as. I'll name it Ahmed underscore T Underscore sorting. Okay, click Save and the location is the following under documents under workbooks. So all our projects are here. Click Save. Now we have saved it. Click Connect to data. So we'll be connecting the same sample superstore. You can click here or Microsoft Excel like this, and this is our data provided by tabu only, the sample data. I'll just click and click Open. Now we are ready with the data, drag the orders sheet from the sample superstore. These are the sheets that means tables in the sample superstore data. I'll drag Here is our data. Okay, while dragging only, you'll be getting the options. I discussed about the initial options which were sought by ascending and descending. So here are the options. I'll just drag it here, click here and these are the options. Currently, it is by default according to data source order. Now I'll click a two z descending. I'll click here. Now you can see it got sorted in ascending order. Now I'll go for descending, and now we have the descending order. Okay. So others are the A two Ze ascending per table. And the last one is Z two a descending per table. So you can sort it accordingly. Now let us move to the next sort the table data example for that click on Sheet one. We have reased the sheet one. On the left the fields of the orders table is visible and our data was sample Superstore. First le double click and rename sort. We will sort the table data under this sheet only. First child drag the dimension category, that is the following to the rows shelf and the sales measure to the columns shelf. Okay, now our bar chart is visible with the sales on the X axis and the category on the YXs. We have three categories furniture, office supplies, and technology. Now, right click on category because we need to sort Click SOT, and now you need to select the sort type. By default is data source order and the B Default sort order is ascending. Okay, in the background, the same is visible. So first, I'll just click descending here and you can see it will be the opposite of this. And it is the opposite. Okay, so this is the sort order. I'll click it again. Now here are the types that is sought by the following. The default was data source order. I'll select field, and after that, it automatically sorted according to the ascending order by the field name sales and aggregation sum. That is in the background. Okay. Now I'll click Close here. Here, what happened? It is now sorted according to the ascending order. That is for the sum of sales. Our office supplies category is having 731 K sales. Furniture more than that, that is 754 K and technology more than the office supplies and furniture with 839 K. So it is sorted according to the ascending order by field. I'll right click again, click SOT. So the previous selection is already here. I'll click descending, and it will be the opposite. Here it is opposite. Click close, and now technology is on the top. That means in the descending order. The highest one is always on the top in descending order. Then comes furniture and the lowest one office supplies in the bottom. Okay. So this was sort by field, right click and click SOT. You can also change the field names here by clicking here. Okay. And the aggregation also aggregation is sum average Max Min and others. We have set the sum here. I'll again set it to ascending by default. Now the changes are visible here. I'll click cross and again, I'll right click and click sort. Okay, we could have done all the changes without clicking the cross, but I just want to show the complete bar chart again. Now I'll sort by manual. So as the name suggests, right now, the sort order is the following. You can also drag it like this. What is the sort order? It's office supplies furniture then technology and the same is visible. Let's say I want technology in the center. What I'll do, I'll just click Technology and use the move up. Okay, the move down will be visible when you go for the top one or the middle one. Okay. When you go to the middle one, all of them will be visible. I'll click Technology and click the Move button. Now our technology is in the center and the bars are also updated. So this is manual sort, right. I did it manually using the arrow buttons. Now the technology category is in the center. So in this way, guys, we can work around the sort. If you want to clear the selections, click Clear. I'll keep it as it is and click Cross. So in this way, guys, we can implement sorting in tabu. I'll go to file and click Save and our project is in the sort sheet under the Amitce Tableu Underscore sorting workbook. Thank you for watching the video. 33. Tableau - Numeric Calculations: In this lesson, we will understand what are numeric calculations in T. We will also see the types and we will also implement an example on Table. Let us see. Consider numeric calculations as an essential for performing various types of data analysis and transforming your data into meaningful insights. Various mathematical operations on numeric fields. To create new calculations is what we call numeric calculations. Okay. We can also create new metrics or insights from this. Some types of numeric calculations include arithmetic comparison, logical, aggregate, advanced and others. Now let us see the types one by one. First, consider that you have two fields. The names are field A and field B for understanding the numeric calculations. The first one is arithmetic calculations, as the name suggests, adding operators like for addition, subtraction, multiplication, division, modulus and exponentiation. So these are all included under arithmetic calculations. Let's say you want to get the sum of sales for three states, let's say, so you can use the following numeric calculation and the plus operator. That is addition. Similarly, you can work around others. Then comes your comparison. Comparison means to compare. That means equal or not equal. It also includes your greater than greater than or equal to, less than or equal. Then comes your logical calculations. That means your logical operators and or not and both the conditions are true. Either one of them is true and not means the reverse condition. Then comes your aggregate. In the previous lectures, we saw that when we dragged our sales, it was sum of sales. And in one of them, we also change the aggregation level to average. So these sum average maxmin are a part of aggregate only. If you want to count the field, you can use the count method. If you want the maximum, let's say want the maximum sales, you can get the max. Similarly for minimum, you can use the min. Then comes your advanced calculation. You can get the percentiles, the standard deviation variance, the correlation coefficient with these calculations. The rank of a field in tableau means to assign a rank for each value within a particular field based on the ordering of values in that field. Now let us see an example of numerical calculations. We will create a new workbook amid underscore Tableu Underscore calculations for all our calculation examples. And for this lesson that is numeric calculations, we will create a new sheet and name it as numeric calculations. Let us see. Here is our tabu. I'll create a new file, go to file, click New. Here it is, the new workbook, I'll close the previous one. Now I'll save it good file save as. I'll save it as Amith underscore, Tableau underscore Calculations. Okay. And the location of your project is the following under my Tableu Repository do documents folder. The file extension is dot TWB that means a Tableau workbook. As you already know, click Save. Now we have saved it, click Connect to data. You can connect any of the source. But if you remember, we worked around the sample superstore, so I can click here or I'll click Microsoft Excel, and I want to show the path again. So this was your sample superstore provided by Tb under the same MIT repository, but the data source is folder. Click here, click Open. Now I'll drag the orders sheet. This was our sample superstore and the tables are here. I'll drag the orders. Now let us start with our first sheet these are the fields of our order stable. Click Sheet one. I'll double click and rename numeric calculations. Okay. All the calculations will be inside this sheet only. I'll create a calculated field using the aggregate function. That means I'll create aggregate calculations. Go to analysis, click Create Calculated field. Now a new dialog box is visible. Click on this arrow. Now all your Functions are visible. Here it is number, string, date, logical aggregate. Since we are working around numeric calculations, I'll click number. These are the number methods. Okay, we just saw some of them. Set the name of the calculation. I'll set it to minimum underscore, sales underscore, ship mode. Okay. Now we will get the minimum sales values for different ship modes. So if you remember for minimum, I just told you in the PPT, we need to use the minimum method, so I'll just click Min here. I double clicked here, and it is automatically showing us the syntax. And the explanation is also here for the minimum value from two expressions. So within this, I need to mention what minimum value I want. Okay, I want for sales. I'll just type S, and it will show me the name of the field. And now the calculation is valid visible here. If it is showing an error, then it obviously means there is an error. Now, you'll get the minimum sales because we have said the formula. Similarly, you can use other methods. AlCl apply, then, on the left, under the measures. Since the sum of sales was also in measures, therefore, obviously the minimum of sales will also be under measures. I should again tell that how do you differentiate between dimensions and measures? Just try to drag any field. Let's say I drag this, and in the bottom, you can see dimension and measures are visible. So our minimum sales are also under measures. So this is our new calculation field. Okay. You can also click Describe here, and it will tell you what is this. It is the minimum underscore ship mode, and it is a calculated field. Okay. Click close. First, I'll drag the ship mode, the exact field to the columns shelf. Okay, now I'll drag the minimum sales underscore ship mode to the rose shelf. AG is visible. That means aggregate. Okay. When you'll keep the cursor, the complete name will be visible. Minimum underscore sales underscore ship mode, which we just created. Now, the bar chart is visible. When you keep the mouse curds at the minimum sales underscore ship mode will be visible. For the second class ship mode, the following is for the standard class, the following for same day, and here is the first class. Change the view entire view, now it's completely visible. So in this way, guys, we can set numeric calculations. Here we have set the minimum sales for a specific mood. And we saved it as Amit underscore Tableu underscore calculation under numeric calculations. In the next lectures, we'll work around string and date calculations, and we will add it in the same Tableau workbook with new sheets. Thank you for watching the video. 34. Tableau - String Calculations: In this lesson, we will understand what are string calculations in Tableau. In the previous lecture, we saw the numeric calculations for numbers. So the string calculations are for text, that means strings. Let us see what are string calculations with some common types of string calculations in Tableau. With that, we will also see a live running example on Tableau. Let us start. So string calculations are used to manipulate and analyze text data to create new insights and add context to your visuals. Some common string functions are being shown below. So we have divided some common string functions and calculations into these types. That means basic text manipulation, regular expression, date, and time calculations, and advanced. We will understand them one by one. Consider that our field names are like field A, field B, field C. Okay, so that we can understand it easily. Let us start with the basic sting calculation. Let's say you want to concatenate the first name with the last name. Let's say my name, you can concatenate a meth with Dan. To make it a complete name, that is amid Divan. You can also extract a part of a string using the substring method. Also, we have the length method to get the length of the string, upper lowercase to convert it from one case to another, trim to remove the leading or trailing spaces. Then we have text manipulation calculations. To replace substring, to split a string into array, to combine array into string, also to extract data from a string using the parse method. So these are the functions provided by Tableau for string calculations. Then comes your regular expression. Okay, regular expressions are mainly used to match patterns for string matching and manipulation, especially in text processing and data cleaning tasks. So here we have some methods for matching the pattern for replacing the matches and for extracting the matched text. Then we have date and time string calculations. Let's say you want to convert string to date, and then date to string. If you also want to convert a string to timestam, you can also do it. A timestam is a sequence of characters identifying when a certain event occurred. It mostly includes your date and time. Okay. So these are the date and time sting calculations for timestam date to string, and date passe. Then comes your advanced calculation to find the index of a substring to check if a substring exists or not. For that, we have the contains method, and then the starts with our ends with method. If you want to check, let's say whether a category begins with the word B or not or ends with the word B or not using these methods, you can implement it. Now let us see an example of string calculations. In the same workbook which we saw under numeric calculations, we will add a new sheet and name it string calculations. Now we will implement the string methods or calculations on Tableau. So this was a tableau. Let us create a new worksheet, click here. So I named it string calculations in the project Amit underscore Tableau underscore calculations. Go to Analysis, click Create Calculated field. Now we will create a calculated field. Click here, and now the methods are visible like before. We saw numeric before number, click string and all the string functions are visible. I'll name it first. Let's say, I'll write it city underscore C. So what we are finding, we are finding the sales of the city that begin with the latest C. For that, what we'll use starts with method. I already told you before. So to avoid any problem, just click here and the syntax. Double click and the syntax is automatically visible. Also, the explanation is visible here with the example, and this is what we'll do. It is right now having errors because we did not addit anything. Here what we want city starting with C. So type city and it's visible. Press enter, comma the syntax is the following. So I mentioned C, that means city starting with C, it will show. That means the sales of the city that begin with the later C because you'll also add the sum of sales measure. Okay. That's it calculation is valid. That means the syntax is correct. I'll also change the code. Let's say, I'll go for double quotes and let's see whether it will be correct or not. Okay, it's working. And the syntax is here. Click Apply, then okay. Now on the left, we have a new field. So city was a dimension, so City underscore C will also be a dimension. The top ones are dimensions and the below ones are measures, I already told you, you can drag anyone and check. Now what we will do, drag the sales to the columns shelf. That is sum of sales and the city to the rose shelf. Now the bar chart is visible for sum of sales by city. Now drag the new field city underscore C to the filters section. After it's visible, we can select the option true or false. So we used the starts with method. That method returns true if the string starts with a mentioned substring. That is, in this case, it was a letter C. So what we should select here, we should select true. So that we want the cities that begin with the name C. That's it. Right now, all the cities are visible. You can see 8-8. Okay, I'll click Apply then ok. And now all the cities beginning with the letter C is visible. So this is how we filtered and we implemented the string calculations. Now only the true values are visible, that means beginning with the letter C. So we have the sum of sales for the cities, starting with the letter C. You can keep the mouse cursor in check. The tool tip is also visible. I'll save it. So, guys, we saw how we can implement the Sting calculations in Tableau, we implemented a built in method and saved the new sheet sting calculations in the Amunderscore Tableau underscore calculations workbook. Thank you for watching the video. 35. Tableau - Date Calculations: In this lesson, we will understand what are date calculations in Tableau. With that, we will also see some common types of date calculations. That is the built in functions provided by Tableau for date calculations. We will also implement such calculations on T. Let us start. So date calculations in Tableau are powerful tools for manipulating and analyzing date and time data. Here we have divided some common date calculations into basic date manipulation, relative date calculations, period over period calculations, and advanced calculations. So for understanding this, we will consider the fields as date field one, date field two, and others. Okay. So these are basically the built in functions provided by Tableau for date manipulation. We are beginning with the date calculations. If you want to get the current date, use the today method. For the date part, let's say it's 25th December 2024, so you want to get the year out of it is a year method. To get the month, use the month, to get the exact day, you need to use the day method. To get the difference between dates, use the date diff method. For adding the dates, use the date ad. So these were basic date calculations. Now to manipulate date, you have date trunk to truncate the date, truncate to month, quarter year. If you want to round down the dates, use the floor method. If you want to round up the dates, you'll use the ceiling method. To format the date, use the date to string method and mention the exact format. These were the date manipulation calculations or functions. Now, these are relative date calculations methods. For getting the previous date, use the today method and subtract one from it for last week, subtract seven, for last month, subtract 30, for last quarter subtract 90, and for year to date, use the following formula. For period over period, that means for year over year, let's say for month over month, these are the methods. That is the dated method, and within that, you need to mention the specific values to achieve the purpose of getting period over period value. Then comes your advanced method. Let's say you want to get the age. So the following is the method. Use the day dif as well as the today method. For next or previous occurrences, use the date add method and within that for previous occurrences, mention minus one. For date range, use the date diff method and mention the range within it, including the start date as well as the end date. That is the range. Now we will see an example to implement date calculations. We already have a workbook emit underscore Tableu underscore calculations, and within that, we will create a new sheet and name it date calculations. We already added numeric and string calculations in the same workbook. So now we will add date calculation sheet. Let us see the example here is our tabu. I'll add a new worksheet by clicking here and I'll double click and rename it. Okay, now we have date calculations sheet in meth underscore Tableau Underscore calculations workbook. Now we will create a calculated field. Click the Analysis menu, then click Create Calculated Field. After clicking calculated field, click here so that all the methods are visible. Now click here to get the date and all the date methods we just discussed are visible. Now, these are the date functions. Let us set the name of the calculation. I'll just set it to date underscore difference. In the previous lesson we also saw, we need to add the formula here. We will find that date difference. Okay. So this is the date difference, and the following is the syntax and explanation with an example. I'll double click and now we have the date difference. First mention a date part, that means the day we mention. Then the start date, start date, we will mention the order date. Then the ship date. After that, mention the start of week, I'll mention, let's say, Monday, and that's it. So what is this day? I'll first give it a quote. So this is a date part. We saw that the date part can be a day here month. Okay, so we have mentioned day here, and here we are finding the difference between two dates, that means the order and the ship date. And the result will be in the day units. The start of the week we have set is Monday. We will get the days it takes to ship products. And that is our formula, and there are no error message. I'll click Apply, then okay. Okay, now we have a field, date underscore difference, and other measures. Now we will implement, drag the region to the rows. Shelf, and the date underscoe difference to the text in the mark shelf here. So this is the date undersco difference, and I'll set it to the text drag it. Okay, now, right click on the sum date difference, that means here because we have sum here. Okay, I'll go to here and click average for the aggregation. We are changing the aggregation level to average. So we'll select average to get the average of the date difference region wise. Okay, that's why we are doing this. Now we have the average. Average date difference is visible. This shows the average days it takes to ship products. In central, it's four. Let's say four days. In East, it's like 3.9. Consider it as four days, South 3.9 and West 3.9. Okay. I can set it to entire view to view it like this or standard. So we found the average days it takes to ship products in all the regions using the date calculations. I'll save it. Thank you for watching the video. 36. Create a Dashboard in Tableau: In this lesson, we will understand what is a dashboard in tabu. With that, we will also see an example to create a dashboard. Let us start. A dashboard in Tableau is a collection of several views, allowing you to compare a variety of data simultaneously. So consider a dashboard as a visual representation of data that combines multiple views, charts and tables. It is an interactive way to display data insights, even trends and patterns. Okay. Remember that in your dashboard, you should have at least three or four sheets. Okay. We will now create a dashboard from sheets that will display various visuals to present sales and profit data across different categories, states, and regions. Before that, let us see the features and benefits of tableau dashboards. As I told you before, you can add multiple views in a dashboard, like let's say multiple sheets, charts, tables, maps also. It will be interactive. So let's say you'll select any of the options in one of the sheets in a dashboard, then the rest of the sheets will also get filtered or changed or drilled down to explore the data. On your dashboard, you can also connect to live data sources so that real time data updates and insights are easily visible. Benefits, the decision making can be enhanced. Obviously, if the dashboards are clear, then it's very easy to track the performance to make some decisions like in which region the sales are more for a specific category or subcategory. With that, the productivity will also increase, because you'll be having a centralized location for data analysis. Collaboration will also increase. You can easily share dashboards with others. Okay, so that collaboration is possible. Now we will see an example. I already told you that we'll be including four sheets. First, we will create a new tabu workbook and name it as Amith Underscore Tableu Underscore dashboard. Within that, we will create four sheets. The first sheet will display the sales and profit for each subcategory segment wise. The second will include the sales across the different states. The third will include a map. In our sample underscore superstore data, we have the data of the US, the map will be of the US and it will display the sales based on state on the map. The fourth will be our underscore region sheet. That means a bar chart that will display sales by region. That is the four regions we have seen before central, east, south and west. Let us create four sheets and then we will create a dashboard. This is our tableau. We will create a new project, a new workbook, codo file, click New. Here is a new workbook. I'll close the previous workbook. Here it is now let us connect to data, the same data. I can click here directly to get the same data or I'll click Microsoft Excel to show you the location again so that it's easier for you. It's in the MI Tableau repository under the documents. Click here, click Open. So you get this with your Tableau. This is your sample superstore and I'll just drag the order sheet. We have three sheets. I'll drag the orders sheet. Here are the records of our orders table. I'll click here Sheet one. I'll double click and rename it to Profits underscore. Sales. Okay. Drag the dimension segment. These are the dimensions and these are the measures. You can drag any one of them and see it's written dimensions and measures. I'll drag the segment to the columns shelf. Then the subcategory to the rose shelf. Okay. Now the measure sales to the color under the marks, and drag profit to the size. Now, heat map is visible. On the right, you can see the sum of sales. Okay. The lighter color means less sales and the darker color means more sales. And the same is visible under the heat map. Profit. The size of each square box is according to the higher and lower profits. These values likely represent different profit levels. We can also change it to entire like this. Okay. Now we have our first sheet. When you'll keep the mouse cursor, you can see the profit sales subcategory and the segment. Okay. I'll save the workbook, file save as. I'll give it a name. Underscore dashboard. Okay, now save it and it will get saved in the following location Mb repository under documents, then the workbooks folder. Click Save. Now we have saved it here. Go for the second sheet, click here. I'll name it to Sates Underscore. Sales sheet. Okay. Now we will set the sales across the different states. So this is our second sheet for the dashboard, drag the dimension state here to the rows shelf and the sum of sales to the columns shelf. Okay, now our bar chart is visible. We can also check the entire view, but I guess standard looks fine. Now click the State field and select sort. Let me sort it by field here and I'll select, let's say descending order. Rest keep as it is, aggregation sum is fine. Field name seals. Click cross. Now we have sorted the sales in descending order, and the state is also visible. Now the sales are arranged in descending order. Now we have two sheets. I'll save. Now the third sheet, click here, I'll name it map because it will be a map. We will display the sales based on state. Drag the state dimension to the detail here under the marks. And it automatically generated the longitude and latitude. That means the map. Okay, it's written generated. Then drag the state again to the label pan so that the state name is also visible on the label. Then the sales measure to the colors pan. Here it is to the color under the mark. And the map is not visible right now. Why? Because it's written 59 unknown. So I'll click here. Edit locations. And here in India, I selected because in the lesson we installed, we mentioned our country as India. It is US, so I'll just select US from here, type and I Type United United States visible. Click Okay. Now the map will be visible. Here it is. Okay. Obviously, you can check the color also. Lesser sales will mean the lighter color and more sales will mean the darker color. So the maximum sales will have the darkest color. That means California here, and it's also New York. So we created the map. When you keep the cursor, the state as well as the sales will be visible. You can go to file and click Save. Then the fourth sheet here, what I'll do, I'll mention sales underscore region. Okay, drag the region to the columns shelf. And sales to the rows. Self, also drag the sales to the label so that a label is also visible. Label here under the marks. Now the labels are also visible. You can change the view, or you can keep it as it is, standard. Now we have the sales for central east south and west region. Our column chart is visible. Now to create a dashboard, firstle Saval. Okay Now we will create a dashboard using all these four sheets. We can also change the color of these sheets if you want. Let's say I'll change the color first. Profit underscore sales, I'll go to format shading. Now the workshot color is white. I can change it to black here. Okay. And for the font, go to format and click Font. Now the font color we want here it is, Let's say I'll go for white. I'll click here. The white is visible. Title because your title is here, I'll set it to White profit sale. Okay. Now, is it looking fine? I guess, yes, I'll keep the mouse cursor and the same is visible. Also these. I'll go to File and Save. Now let us go to the second one, Shades underscore sales. I'll do the same format, shading, worksheet color black. Okay, and format, then font. Header, I'll set it to white and title I'll set it to white again. Okay, this looks fine. Now go to the map. This is our map. How we can change the background. Let's say you want a darker map, I'll right click here and click background layers. Here it is. It's a lighter one, I'll go for dark let's say. If you want to show the outdoors and streets also, you can do it like this or the satellite. Okay, I'll set it to dark. Okay, you can also change it, but let's I'll keep it as it is. For map, now, I'll go to format, Shading and you can see the workshot color. I'll set it to black, let's say. Okay, this looks fine. And here for the font, I'll go to format, click font. What is this? This is the title. I'll set it to white. Okay? If you want to zoom in, click here. Okay, if you want to zoom out, you can click here. Now sales underscore region, I'll do the same. Go to format, click Shading, set the worksheet as black. Sales underscore region, go to format directly. Click Font. Title, set it to White. Header. White. No, this looks fine. Okay. I'll go for entire view, let's say. Okay, now we have all our four sheets. We will create a dashboard. You have new worksheet option here, you already know. But in the center, you have a new dashboard option. Click on it. Here is your dashboard option. You can go to Format first and click on dashboard to set the color of your dashboard. Let's say, I'll give it a color, click more colors and click here. Let's say this will be your color of the dashboard. Okay, and this is the color. Let us add a title. I'll drag it here. Now I'll set the view. I'll go to size and set automatic so that it is now completely visible. From here, only drag the text and take it here. Let's say, I'll mention performance in sides. Color, I'll mention white and font, let's say, 14. Let's say 15. Okay, and click Okay. Now it's visible here. Right click format, text Object, alignment, top here. That's it. Okay, now this looks fine. I double clicked on it, and I'll mention this. Okay. Let's say I'll also set it bold, that will look fine. Okay. I'll close this and the sheets are visible. When you keep the cursor, the sheets are visible as a tool tape. First AltrackPfit underscore sales. Yeah. Okay, it's visible here. Then states underscore sales. I'll take it here. Okay. Now comes your map. I'll drag it here. Okay. And the last one, your sales underscore region, I'll take it here, let's say. I'll just take it upwards. Right Edit text. Let's say, I'll change the color to more colors and this. Okay, now it's visible. Right, click and select floating. I'll drag it to here, right click. Floating. Okay. Take this here and right click floating. Take this here. Okay. And I'll completely drag it to here. Take this here and take the profit here. I'll center align it. Okay, now we have a dashboard. We can also change the name from here or we can directly click here and select this to go to the sheet. It will take you to the following. You can also fit the sheet. Let's say, I'll go for standard, and it's visible like this. Okay. But I'll again change it to entire view. So the first one profits underscore sale was Profit and sales by segment. Okay, and I'll remove the sheet name. Apply. Let's say, I'll name it profit and sales by segment. Okay. This is sales underscore region. That means the fourth sheet. I'll double click and mention sales by region. I Okay. Now, this was States underscore sales sheet. That means the second sheet. I'll double click. Sales by States. I'll remove the sheet name. Okay. Sales by States. And the last one map. So this is the map of United States. And it was the third sheet map. Here it is, it was the third sheet. I'll double click map displaying sales US Map displaying sales. Click Apply Okay, or dashboard is ready. Now, I would be wondering how we can make an interactive. I'll make an interactive dashboard now. Under profit underscore sales, that means the first one. What I'll do? I'll click on it first. Okay. Now click use as filter. That's it. We have set now when I'll click any of the value, let's say, I'll click on art. Here, the third one. What will happen? All of the values updated for the art subcategory. Okay. I'll click, let's say on Chairs. Okay, this is a chair. You can see the tool tip right, consumer hairs profit sales. When I click on it, the sales of the Chairs subcategory updated everywhere. I'll click plus here, and you can also see the map and the sales Pi State is visible. All the four sheets are interactive. We can go to file and click Save and our dashboard is under this. Okay. So this is how we can create a dashboard. A here, you can rename the dashboard. I'll just double click and rename it to let's say Superstore dashboard or store dashboard. If you want to add more dashboards, you can click here again. So, guys, we saw how we can create a dashboard in. We created four sheets and addited as a dashboard. We also made it interactive. I'll click here, let's say, and all the four sheets will update. Thank you for watching the video. 37. Create a Forecast in Tableau: In this lesson, we will see how to create a forecast with T. With that, we will also understand the features of forecasting as well as the best practices. We will also try to forecast the profit for the next three years with T. Let's see. So forecasting means allowing users to predict future trends and patterns in their data. So we will forecast the value of the major profit for the next three years. In this lesson, forecasting involves predicting future data points by analyzing historical data. It helps in identifying trends and make data driven decisions. So before using our sample store data to predict, we will first see the features and best practices of forecasting Tableau allows you to automatically select the best forecasting model based on a data. When you connect your data source and forecast, it will automatically select the best model. With that, it will also add the confidence intervals to indicate the uncertainty associated with the forecast. Consider a confidence interval as a range of values that is likely to contain the true value of the forecasted data point. It gives an estimate of the uncertainty or variability around the forecast. With that, you can forecast multiple time series at once. This means generating forecasts for several related datasets simultaneously. This is useful in scenarios where you need to predict outcomes for multiple categories, products, regions, et cetera. Now here are the best practices for forecasting. Use a sufficient amount of historical data. So it is preferred to include a minimum of two to three years of historical data, and the forecasting model should be correct. Tableau will automatically select it for you, but you'll also have different options to choose from. You should also monitor the forecast. Now let's see an example. We will create a new tabu workbook met underscore Tableu Underscore forecast and we will forecast the profit for the next three years. Let us see. Here is a Tableau we just created the dashboard. Okay. I'll create a new workbook, go to file, click New. Now workbook is visible. Let me close rest of them. Now I'll save it file, save as. Amtnderscore. Tableu Underscore forecasting. I hope you remember tabu workbooks get saved in the My tabu repository folder under the documents. Okay, so I'll save it. Now connect to data and we will connect the same sample superstore. I can click here also directly, or I'll go to Microsoft Excel so that I can see the path again. Your data source provided by Tableu itself is in the My Tableu repository data sources folder, and this is the sample data. Okay, click Open so here is our data. The sheets are visible on the left. That means the tables. I'll drag orders. And this is the fields for the order table. I'll go to Set one directly and double click and rename forecast. Now let us begin. Now first drag the order date to the columns and then drag the sum of profit to the rose. Now the line chart is visible, you can also change the view to entire view. Here it is 2021-2024. So this is our historical data now because we will use it to predict to forecast. Go to the analysis menu, click on it. Here click forecast and after clicking, Show forecast is visible. I'll click on it. Now after clicking, you have the forecast on the same line chart. Here is the estimated profit. You can also keep the mouse cursor. So it is predicting the profit by default. I never added the duration also. To add the duration, right click the forecast line chart here. It is selected, click forecast and here you can check the forecast option and describe the forecast. First I'll click the forecast options. Now you can set the forecast length. The forecast model. As I told you it will automatically set it for you. I'll set it to exactly three years. You can also set the quarter month, even days for the prediction. The forecast length is now three years. Click Okay. Can also set the prediction intervals, but I'll keep the default and click okay. The forecast is visible. You can check it predicted for the next three years 2025, 26 and 27. Okay. Now, describe the forecast. If you remember, you can click here and click forecast and describe forecast. Now the forecast is visible. It is based on the past data, 2001 to 2024. The past data is also visible here here, 2001 to 2024. And the changes are visible here. You can also copy and the time series and measure is also visible. And here are the models. Okay, click Close. So here the color is also visible, the actual and the estimated. Okay. Change the color from here, click here and click Edit Colors. You can assign a palette if you want like this. I clicked on it and assigned the palette, click Apply, and let's see the changes. Now you can easily differentiate. The actual one, the estimated one is here. So in this way, guys, you can also forecast, we saved it. So, guys, we saw how we can easily forecast wet W. We predicted the profit for the next three years W W, thank you for watching the video.