TABLEAU 2018: Hands-On Tableau Training For Data Science! | Kirill Eremenko | Skillshare

TABLEAU 2018: Hands-On Tableau Training For Data Science!

Kirill Eremenko, Data Scientist

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70 Lessons (8h 4m)
    • 1. Promo

      1:40
    • 2. Welcome! What is Tableau & Course Overview

      8:28
    • 3. Installation

      4:06
    • 4. Exercise - Get Excited!

      5:01
    • 5. Section 2: The Business Challenge - Who Gets the Annual Bonus

      3:41
    • 6. Connecting Tableau to a Data file - CSV file

      6:05
    • 7. Navigating Tableau

      8:53
    • 8. Creating Calculated Fields

      6:25
    • 9. Adding Colors

      7:46
    • 10. Adding Labels and Formatting

      11:07
    • 11. Exporting your worksheet

      6:24
    • 12. Get The Viz

      1:11
    • 13. Section 3: Intro

      2:20
    • 14. Working with Data Extracts in Tableau

      8:06
    • 15. Working With Time Series

      9:41
    • 16. Understanding Aggregation, Granularity, and Level of Detail

      9:28
    • 17. Creating an Area Chart and Learning about Highlighting

      8:53
    • 18. Adding a Filter and Quick Filter

      8:56
    • 19. Section 4: Intro

      1:19
    • 20. Joining Data in Tableau

      10:00
    • 21. Creating a Map, Working with Hierarchies

      11:08
    • 22. Creating a Scatter Plot, Applying Filters to Multiple Worksheets

      10:23
    • 23. Let s Create our First Dashboard!

      7:24
    • 24. Adding an Interactive Action - Filter

      8:28
    • 25. Adding an Interactive Action - Highlighting

      9:32
    • 26. Section 5: Intro

      4:31
    • 27. Understanding how Left, Right, Inner, And Outer Joins Work

      6:25
    • 28. Joins With Duplicate Values

      2:39
    • 29. Joining on Multiple Fields

      5:30
    • 30. Data Blending in Tableau

      15:23
    • 31. The Showdown: Joining Data v.s. Blending Data in Tableau

      10:55
    • 32. Dual Axis Chart

      12:15
    • 33. Creating Calculated Fields in a Blend (Advanced Topic)

      13:12
    • 34. Section Recap

      7:09
    • 35. Section 6: Intro

      1:01
    • 36. Downloading The Dataset And Connecting Tableau

      4:01
    • 37. Mapping: How To Set Geographical Roles

      6:36
    • 38. Creating Table Calculations for Gender

      5:09
    • 39. Creating Bins and Distributions for Age

      6:37
    • 40. Leveraging the Power of Parameters

      7:46
    • 41. How to Create a Tree Map Chart

      2:19
    • 42. Creating a Customer Segmentation Dashboard

      6:09
    • 43. Advanced Dashboard Interactivity

      4:20
    • 44. Analyzing The Customer Segmentation Dashboard

      10:57
    • 45. Creating a Storyline

      12:39
    • 46. Section 7: Intro

      2:14
    • 47. T20What Format Your Data Should be in

      5:15
    • 48. Data Interpreter

      11:26
    • 49. Pivot

      2:46
    • 50. Splitting a Column Into Multiple Columns

      3:20
    • 51. Metadata Grid

      6:58
    • 52. Fixing Geographical Data Errors In Tableau

      7:23
    • 53. The Challenge: Startup Expansion Analytics

      8:10
    • 54. Custom Territories via Groups

      9:15
    • 55. Custom Territories via Geographic Roles

      4:31
    • 56. Adding a Highlighter

      5:46
    • 57. Clustering in Tableau

      7:08
    • 58. Cross Database Joins

      8:21
    • 59. Modeling With Clusters

      11:55
    • 60. Saving Your Clusters

      3:32
    • 61. Design Features

      3:57
    • 62. Section 9: Intro and First Challenge

      2:50
    • 63. Data from PDF files

      4:20
    • 64. Connecting to PDF

      9:28
    • 65. Connecting to Spatial Files

      7:04
    • 66. Joining to spatial files (and data integrity)

      9:07
    • 67. Putting it all together

      6:07
    • 68. Step and Jump line chart

      7:28
    • 69. Viz in Tooltip

      8:30
    • 70. Section Recap

      4:54

About This Class

Learn data visualisation through Tableau 2018 and create opportunities for you or key decision makers to discover data patterns such as customer purchase behavior, sales trends, or production bottlenecks.

You'll learn all of the features in Tableau that allow you to explore, experiment with, fix, prepare, and present data easily, quickly, and beautifully.

Use Tableau to Analyze and Visualize Data So You Can Respond Accordingly

  • Connect Tableau to a Variety of Datasets

  • Analyze, Blend, Join, and Calculate Data

  • Visualize Data in the Form of Various Charts, Plots, and Maps

Convert Raw Data Into Compelling Data Visualisations Using Tableau 2018

Because every module of this course is independent, you can start in whatever section you wish, and you can do as much or as little as you like.

Each section provides a new data set and exercises that will challenge you so you can learn by immediately applying what you're learning.

Content is updated as new versions of Tableau are released. You can always return to the course to further hone your skills, while you stay ahead of the competition.

Contents and Overview

This course begins with Tableau basics. You will navigate the software, connect it to a data file, and export a worksheet, so even beginners will feel completely at ease.

To be able to find trends in your data and make accurate forecasts, you'll learn how to work with data extracts and timeseries.

Also, to make data easier to digest, you'll tackle how to use aggregations to summarize information. You will also use granularity to ensure accurate calculations.

In order to begin visualizing data, you'll cover how to create various charts, maps, scatterplots, and interactive dashboards for each of your projects.

You'll even learn when it's best to join or blend data in order to work with and present information from multiple sources.

Finally, you'll cover the latest and most advanced features of data preparation in Tableau 10, where you will create table calculations, treemap charts, and storylines.

By the time you complete this course, you'll be a highly proficient Tableau user. You will be using your skills as a data scientist to extract knowledge from data so you can analyze and visualize complex questions with ease.

You'll be fully prepared to collect, examine, and present data for any purpose, whether you're working with scientific data or you want to make forecasts about buying trends to increase profits.

Transcripts

1. Promo: hello and a warm welcome to the course on Tableau. My name is Carol. Remain CO and I will be your instructor. And first off, how is the scores Different. Well, I like other classes out there. This course is truly step by step. And already after the first section of this course, you will be able to start analyzing tab. Then in the second section will go into more depth there, some additional skills and still cement in the ones that we've already picked up in the third section will go into more debt and so on. And you will see how you're getting better and better with every step that you take in this fourth. And also in this course you will learn by doing every single module in this course is that you don a set and you visual and then you exercise for you. So let's have a sneak peek at some of the powerful officials that you'll be creating in sports. In this course, we will be working of the full suite off visuals you can possibly imagine tablets starting from your bar charts and moving onto line charts and area charts. Right there. We turned a line chart into an area charter. We're adding some labels to make you look fantastic. We will work with maps. Lots of different maps of the US UK will add scatter plots to those maps. And I'll show you how to include those maps in powerful dashboards. And you will see how easy it is to create dashboard. And we will even look at storytelling will show you how to create a story line on fully leveraged with power, which is within tableau. Does that sound like something you'd be looking for? Well, then don't put it off like take the scores but now and join the cloths and I look forward to seeing inside. 2. Welcome! What is Tableau & Course Overview: hello and welcome to the course on Tableau. I'm so glad to see inside. We're going to have heaps of fun along the way, and I promise you that you will learn a ton. And in this short tutorial, what I wanted to do is give you a quick overview off what tableau is and what it's used for . And then we will go through the sections of the course, and I will show you what to expect in each section so you can navigates your way through the course much easier. So let's jump straight into it. Tableau is a very simple, yet powerful tool for everything to do with Donna. The company's mission is to help people see and understand Donna. And as you can see here, Tableau is a completely dragon drop software and using tableau, you can create visuals sometimes 10 times faster than you would have created them in other programs. And overall travel is a new and innovative approach to business intelligence. In terms of structure, the course has a spiral structure, and what that means is that with every new section, you move up a level in the spiral learning new skills and techniques while still repeating and cementing in the older ones that you picked up earlier. And so let's have a look and see what we have here in the first section. That's the one we're in right now. You will install tableau and then a radiant lecture. Three. You will see how you can create a powerful visual, and, moreover, you will create it in under five minutes. And it's this same visual would have taken hours to create using other tools. Then, in Section two, we will talk about the basics of tablets. I'll show you how to connect to different daughter sources. Um, we will navigate tableau. We will learn how to create calculated fields. So it's an important topic, and I specifically included early on in the course so that we can play a round of calculated fields along the way as we learn new techniques. Um, we'll talk about colors formatting and exporting your results so all the basics will be covered off in this first section on. After that, you can already start applying tableau. Start applying the basic level of tableaux in your work. If you required to do so, Um, then in section three, we will go into a bit more depth. We'll start talking about time Siri's, which is an important part of working of tableaux, so visualizing trends and how things change over time. We will talk about filters, but most important in this section we will talk about aggregation, aggregation and granularity. So it's this lecture. We're here and there you will see how tableau operates and what concepts are behind the Tru was happening in the background when you're dragging and dropping things into the charts. So it's important lecture because it's important to understand how the two works to take full advantage of it going forward. Next in Section four, you will already create your first dashboard. That is how quickly will get tougher as dashboards, so we will create maps. A map will create a scatter plot, and then we will combine them into a powerful dashboard depicting sales of a certain store . And also we will add interaction, interactivity toward dashboard tool at an action which the filter and highlighting, and you will also see the difference between filtering and highlighting. Then, in Section five, we will kind of take a step to the side and we will talk about joining and blending, so I will give you a full introduction into what joining is so left. Right? Inner outer joins what happens when joins move duplicate values, and one happens when you're joining in multiple fields. So I do understand that perhaps you are not coming from an SQL background. You might not know everything about joints, so that's why we cover it off in the 1st 3 lectures. And then we will talk about daughter blending in tableau. And finally, a lot of people are, um, after this topic. What is the difference between joining and blending daughter and when to use what we will definitely cover that off. So you are a pro in knowing when to use the joint and two inches of blend. Also in this section will cover off a dual axis chart, which is important and will have an advance topic here. Creating calculate feels in a blend, so I've included it here. You don't have to do it if you feel that you're not radio, you don't really need this ah, information. But whenever you do see that you need this specific skill in trouble, you can always come back to the course and watch this lecture again. Then after that, we move on to the big guns. We're talking here about creating and a customer segmentation dashboard. We're introducing lots of new skills, like table calculations, creating bins using parameters set in geographical geographical roles. At the same time, we're creating lots and lots of new charts, and then we're putting them all into it segmentation dashboard, which will be very powerful. Then we will analyze this dashboard, and you will see how businesses can take advantage off this and service that customers better by looking at Donna. And then we will create a storyline. So storylines and new feature that was introduced in Tableau 8.2. And here you will learn how to I take full advantage of it and presenting audience in the best possible way. And finally, at the end of the course, we'll talk about advance daughter preparations. This is kind of a bonus section that I've thrown into the scores because daughter preparation is important. A lot of new features were introduced that allow you to simplify the process off Donna cleaning and preparation four year analysis, so definitely, and the violin section or more over important section because this is something that has to be done every single time. But it will get you going through your analysis much faster. And then in Section aid will be looking at clusters, custom territories and design features. So you were gonna have a brand new challenge is going to be an exciting challenge where we're going to be helping a start up with some of their expansion analytics. In this section, we're gonna cover of quite a lot of interesting topics such as Custom Territories will learn how to do clustering, analytics and tableau and even across database join. We'll learn to ways to perform custom searchers by groups and by geographic roles. And then we'll talk more about these features. And specifically, will DeLillo devote a lot of time and attention to clustering and tablet because that's an ultra powerful future and also will talk about other features such as highlighter and then some new design features and some mobile features. And all in all in this section, we're going to solve a very fun and exciting business challenge for this startup. And then finally, will a wrap up the course of Section nine. This section will be presented by Jean Pierre Alevis, Cocky, Who is the tablet structure here at Super Day Science, and he'll be presenting the new and exciting features available within tableau 2018. I will hand over to Jean Pierre to walk you through this section. Now. Thank you for the introduction, Curiel. I am super excited to be presenting the sport of the section and cannot wait to get started . We will be looking at two business challenges within the specific section. Now, firstly will start off by looking at what happens when the only available data we have is from a pdf. We will be connecting to the pdf and extracting the data for right from inside tableau. Yes. Who knew it was possible right from? They will be looking at using special falls which will be required when the tabler built in ST off. Geographical roles are not sufficient for this specific business challenge. Talking about the challenge, we will then dive right into solving it, and we'll be looking at the safest box with in New York City using a real life data after the business challenge will be looking at one of the excellent features and one of my favorite features within tableau. Their visit in Filter This is a new way to build and interact with your visualization to progressively review additional details about your data really, really handy. We'll finish the section off by looking at useful improvements that the blow has made in the last couple of versions. Firstly, by looking at the upgrades on how tableau stores that and what the benefits are of that we were looking at downgrading the workbooks. When you're working in environment, where different visions off their blurry is being implemented and lost, he will be looking at some improvements to the way stories are being used in Tabler. I am super excited, cannot write for the section and I will see you then. 3. Installation: Hello and welcome back to the course and tableau. And in today's tutorial, we're going to stole tableau onto a computer. So what do we need to still tablet? Well, the only thing that will need is a browser. So let's go ahead and bring that up and where you will need to proceed to is www dot tableau dot com. Now you have two options. Here you consult tableau and get a demo version of tableaux. That's of course, if you don't have a full licence of tableaux already, if you have full license of tableaux ready, then you can proceed with the first option and then use your license. Otherwise, if you don't have a full licence, you can either use a trial version off Tabal. They provide a 14 day trial. Or you can use tableau public, which you can get at public dot tableau dot com. So we're going to start with option number one and then I'll explain a bit more about tableau public. Now what we need to click is the try and now button up at the top. Once we click that here, we can download our free trial and in order to do that, we're going to need to enter our email. Onda. Let's for argument's sake, put in email test 123 at gmail dot com and click Download Free Trial. And now, as you can see, your tableau installation has started downloading. So I'm going to cancel this one because I already have tableau installed on my computer. Onda. Also, you will notice that there are a couple of versions, so the version has been downloaded is the one that has been recognized for my computer. That's a 64 bit Windows version. If you need a 32 bit version for Windows, you can get it here. Or if you need the Mac version, you can get it here as well. But normally the website will recognize the correct version that you need and download that one right away. So there you go. And once you have downloaded the installation package just in Seoul tableau, select a 14 day free trial and proceed with the problems. After that, you will get an icon on your desktop. Now, if you want to proceed with the tableau public version, then you'll need to go to public dot tablet dot com and Tallulah public is absolutely free , so it doesn't have a limitations in terms off the amount of days that you can use it for. It's a completely free software. It does have a few slight restrictions. For example, you can cannot create extracts, and you cannot save files directly onto your computer. You'll have to save them onto the public table public server. But that is not a a big hurdle in terms of completing this course, you will be able to totally complete this course. I've done it myself. I've created the most complex physicians in this course using tableau public, and you can totally do that as well able public is a very convenient tool. It is free, and it is often used by people like journalists and professions where they're not facing any sensitive daughter, where they just want to create some really interesting visualizations that they want to share with the world. So tell the public is a great option. Often get asked what is the best way to take this course? If the travel oh trial has expired or if somebody decides that the trial is not long enough , Tabal public is a great option to complete this course. So it's select one of those two. I dislike tableau. I'll be using Tableau the full version throughout the score. So if you like to fall along exactly that, it's like the tablet full version. If your trial has expired, or you just want something that doesn't have a time limitation, go of total public and you'll be able to follow along with 99% off this course as well. And once you've installed tableau, you'll get a just a Pichon just like this one. So if you double click it, that will bring up tableau on. This is what it looks like inside. And this is where we'll get to the fun stuff and we'll proceed with that in the further tutorials. All this course I call way to see you next time. And until then, happy analyzing 4. Exercise - Get Excited!: Hello. This is Carol from super dot assigns dot com And welcome back to the course on Tableau. So what's up with the time? Marie Osk? Well, the thing is that I'm super excited about you taking this course. In fact, I am so excited that I really, really want you to get to the end and get the maximum value out of this course and learn how to use Tabal like a pro. And so therefore, I've challenged myself to get you enthusiastic about this course in under five minutes, and that's exactly what we're going to do today. And I'll just give you a quick overview. We're going to look at a massive data set and I will show you what you can do using the power off tableau in a very, very short limited of time. And I hope you that will get you excited. All right, let's get started. First of all, we'll need a browser. I'm gonna use chrome and at the top, just type in, um, in this in address bar, you need to go to super datta science dot com slash tableau. And that's where all the daughter sets for this course are located, and here you can get the one for today. It's called The Superstore Us. So just download that I'm going to save that into my tableau course folder as good and let's bring up that folder. So there's a the data set. We don't need the browser anymore, and we still have three minutes, 45 seconds. Let's open, the daughter said, And have a look. So what? This is not a city represents is a list of transactions for a store for AH, 2015 from the start of the year until announced that for the first half of 2015 and here you can see every single transaction the store Ah has made for this year. Veterans. Every transaction is represented by a row here. So, for instance, um, the Ro I ds tells you the number of the transaction. The discounts unit price, shipping cost customer ready, a lot, a lot of information. And at the end here, it's got ah, the profit for this specific transaction. So here, for instance, it's $4000 or minus $53 and it's also broken down in by column. It says This is all United States and got region state up Roman city. And if you look at this daughter said, it's actually quite massive is got 1953 Rose on the question has been asked, is Can you quickly tell us what are the most profitable and the least profitable states? According to his daughter Set and also plus a map right now create a map that will show us very quickly how the states of performing. And you have to do that in a very limited time, in fact, in under 2.5 minutes. So let's get straight at it. I'm just gonna close the Excel spreadsheet here. Close this folder, and now I'm going to open tableau, and we'll see how quickly we can do this. Two minutes left. Continue. Okay. So just fall in my steps, I won't explain, um, every single step. But through this course you will learn all of this and even more So now we're going to connect a data source over here on the left Click Excel. Find your daughter set, double click on it. It's opened up now. Now on the left. Choose the orders tab and drag it into this white space, and right away you can see a preview of the spreadsheet appear in front of you. Next click this orange button here, which says, sheet one. And here you've got to Tabal Workspace, which right now is empty. We need to put some stuff in here. How much time? One minute. 40 seconds. Okay, let's do this. All right. So what we're going to do is we're gonna find country, and we're going to drag it in the middle of this white space here. Oh, look, a map of heared while tableau is quite smart. Okay, so now we're going to look for, um, State of Province, and we're also going to drag it onto the map. Oh, well, look at all these adults appeared in the different states of the US. Okay, So what are we going to do now? We're going to take profit because we were asked about profitability, and we're going to drag it onto color. And next, we're going to take profit, and we're going to drag it also onto label. Now we're going to click label, and we're going to click the forint, and we're going to change the phone size to 12 and that's it. How much time do we have? We have 58 seconds. So that was all under four minutes. And what can we see here? We can see that right away just by looking at this map there. It's so intuitive. We didn't even have to specify any colors or anything right away. We can see the least profitable state that will. The most losses were incurred in North Calera, Ala. Carolina. And the most profitable state is California Right away. You can tell those things, and also you can even give more insights. According to the map, these Selvin states are not doing that well in this region except for maybe Georgia and the Northern States. And over here, the Western state Western states are doing better, except for Montana. And all of that was done in under five minutes. Hope you're super pumped, super excited. We will learn all of this in the scores and much, much more. And you will definitely have fun through the way I look forward to seeing you in the next section and until next time, happy analyzing 5. Section 2: The Business Challenge - Who Gets the Annual Bonus: Hello, This is Curole and welcome back to the course and tableau and congratulations on completing the first section of the course on, more importantly, on making this step into the second section, I'm super excited that you're here, and I hope you are as enthusiastic as I am about the material that we have ahead of us in this section. We have a really business problem, a real challenge ahead of us, and let's have a look at what it is. So here's a document that specifies the challenge. Let's have a look. Ah, it's end of financial year and that mean it means it's time for annual bonuses. The store, which we're looking at the store operates in the three regions and only the top performing employees in each region qualifies. For a bonus. Find out which three employees are eligible to get a bonus to get bonuses for this year. Employees are measured on the total number of total value of sales, and the daughter, as we discussed, is located, um, at this link. So here's the website and you condone load the daughter here. So just a quick word of caution. If you're using just ah normal windows. Get this first file. If using, Mac, get the second file. And if for some reason, for whatever reason, you will experience, um, problems with either off these CS three files, then just go ahead and download the third file and proceed as we did in the previous section within Excel data source. But do let me know and I will definitely, um, do everything I can to help you out to make sure you can't. You're able to work with CSU falls as well, because they are quite common. So save link as and I'm great decided to my table. Of course. Folder save. There's the file. So what a C three file is? It's basically a text file, but it's, um, daughter separated by commas. And that's why it's called a comma separated values file. That's what CSU stands for. So let's open that up and have a look. Okay, so this file contains once again transactions, um, and split by region. It's got the representative name. So the person who conducted that transaction, what he sold So this is a stationery shop and office supplies shops so they sell pens, binders, discs sometimes and the number of units that were sold and the unit price. Um, so this is a much smaller file, only 44 rows, including the head. Or so it is a very basic ah sample file. And but it is good is good to start with this because it will help us understand exactly how tableau works. And moreover, if you do have anything that you're curious about, you can always come back into the file and have a look for yourself and even just filter out that information that you're looking at in tableau and just compare. So it's a very good, very small, very good file to start exploring tableau with. That's exactly what we're going to do. So in this section we've got quite a lot of ahead of us. Ah, we're going to be looking at awesome things like creating own calculated fields will be working of colors will be adding, labels will be formatting our chart exporting our worksheets and, uh, all of the basics. We're going to cover them in this section, and that will create a great foundation for us going forward. So we'll get started in the next tutorial, and I look forward to see you them until next time. Happy analyzing 6. Connecting Tableau to a Data file - CSV file: Hello. This is Curole and welcome back to the course on Tableau. And today we'll be connecting our daughter source to Tableau. So I'll bring up tableau. And this is the daughter source that we're talking about office supplies. So we downloaded in the previous lecture, and normally throughout this course, I won't be spending ah lot of time on connecting two Adanaspor because, as you'll see, it will become kind of a quick thing for us will be doing it pretty much on the fly. But today I thought I would stop on it specifically because we did rush through it kind of last time, and I didn't have a chance to show you around the connection manager interface. So let's go ahead and do that. Um, as soon as you open tableau here on the left, you have a column called Connect, and it's got different types off files you can connect to. So last time we did an Excel file, but this time, if you have downloaded the CSP file, see his fee files actually considered a text file because it's basically text delimited by commerce. That's why it's called CSC comma separated values. So let's click on text file, and now we will select our file here. Office supplies. Does CSB and we'll open it up and right away we were redirected to the connection manager for this daughter source. And let's have a look around here. So on the left here, you've got a directory where the files located and at the bottom. Here, you've got only one file currently. That's because we only have one file in that directory. Later on through the course, you'll notice that when we have more files of the same type, there will be more there will be listed here and you'll be able to select from them. So here you've got a window where all the files you have selected are located. And so what does that mean? Well, that basically means that you can select many files. So, um, I can show example. Now I can drag another one of these into here and right away something happens. Tableau is trying to find a way to connect these two files and basically joined them. But we won't do that now. So it was Just click the Red Cross here and cancel that we will talk about joining daughter further down in the course. But just bear that in mind that, um, your daughter that you're working within tableau doesn't all have to come from one file. It can come from many files or can come from many tabs in a file, or it can come from different types of files. But once again, we will talk about that later on. Um, at the bottom here, you've got a preview of your file so sudden rows and columns off the files just so that you can have a look and see what you're dealing with. And in our case, we do have the order date, which correctly here has been identified as a date. So you can see this, Aiken. That's a date, Aiken. Then these are have been identified as text, and these have been identified as numbers. And here there are some more controls which we will talk about in further sections of this course and up top here. Also an important part of the connection manager, the live or extract connection. Once again, we will have a separate lecture on that, and we will understand what the difference is and when you would prefer to use an extract for now. Let's just leave it at life. So everything looks good over here and now we can proceed onto the dashboard so we just have to go here and we'll talk about all this in the next section. I just wanted to show you here that we have a daughter column, and here we've got our data source. So this little icon is a Nikon that is used. Teoh Illustrated Daughter base. If we right click on it and click View daughter, you will see our daughter just as we saw in the previous window. The columns can be rearranged here that there is, That happens, That's that's totally normal. Um, but this is like a preview of it. The daughter is just as we had before, so that's pretty much it. That's as easy as it gets to connect her daughter source. And before we finish up this lecture, I just wanted to show you one more thing. So if I want to connect to more data sources, I can always go here. I can click. Just go back to the daughter source connections over here, or you can just go Datta new data source and connect from here. So if you want to connect to another daughter source, you just click this icon away here. But what we are looking at now is the types of data sources that Tabal can work with. So as we discussed, there's Excel. There's a text file, which includes CS three files. There's access databases. There's now statistical files. You are able to connect to statistical files, and, as you can see here, these air sass files, SP, SS files and even our files. For those of you who are interested in statistical modelling with our, um, let's have a look. What else we have have got tableau server files. We've got micro cept Microsoft SQL Server. So we will have an example of this in the course. There's my SQL databases for online. Use his oracle, and there's lots of other different types of service here. So if you are doing, for instance, Hadoop and Big Daughter analytics, then you've got a pivotal green plum databases. Post grass girl Andi even have sap Hana here. So as you can see, tableau guys are constantly introducing new connection to connections, to tableau and trying to keep up to date with the technical trends. So that's just even if you don't use any of this just good thing to have, you know, kind of in mind to know that tabloids not this to little, become obsolete one day. It's always changing and always adapting to the market and what's happening. All right, so that's it for today's lecture. We did connect very quickly. We just had a lot of discussions about other things going forward. In the course. Connections to data will be much faster. So there you go. And I look forward to seeing you next time. Until then, happy analyzing. 7. Navigating Tableau: Hello, This is Carol, and welcome back to the course and tableau. In today's tutorial, we will learn how to navigate tableau, and we'll get to play around the tool. So here you can see where we left off. Last time we had just connected to our office supplies that CSP daughter source. So let's move on to the tableau workspace. Here you can see at the bottom a tap cold sheet. One lipstick on that and right away were presented with the tableau working area, and it may seem a bit overwhelming at first, but that's exactly why, in the previous section, we had this quick, agile run through where we very rapidly created a map, and it was quite intuitive, wasn't it? So that's exactly what we'll talk about today, how easy it is to navigate Theis workspace in front of us. So the two main areas here are the daughters connection on the left or the daughter tab on the left and the working area on the right. So this is where you will be creating things masterpieces. So let's talk about the daughter tab on the left. First, the daughter is always broken down into two sections, dimensions and measures, and there's a very distinct difference between them, and it's important to understand. So dimensions and measures are roles different, two different roles that any Donna element can take. And normally what tableau does is in Mitt into measures. It puts any kind of miracle values, and in two dimensions it puts all the categorical on and kind of qualitative donna. So that's the default setting for tableau, and you're easily able to drag them around. So if you're not happy of something being a measure you want, you can put into dimensions like like that, for instance, as easy as that. But we won't do that right now, so I just quit controls at their to undo inaction. It's, Ah, the standard Windows key to cancel something. Um, so the other way to think about dimensions and measures is dimensions are independent variables and measures are dependent variables. So, for instance, you have here we have units, units. So how many units all of a sudden item were sold? And here we have region so we can find out how many units in each region were sold, so region will be the independent, bearable and units will be the dependent variable because it will be grouped by region. And based on that definition, which is a correct definition, things might be you might, you might require to move things around from dimensions into measures and measures. Two dimensions. But we won't focus on that right now, because tableau usually guesses it quite correctly. Okay, so what do we have here as well? At the top, we've got the normal ribbon for windows. So file basically, Consejo, your file open and you file daughter, you can collect connect to new daughter sources here. Worksheets. So this is considered a worksheet. What we're going to be creating now is going to be a worksheet, and we will get to work with these elements a bit more in the future. Dashboards. We are not talking about dashboards right now. It will come further down in this course and dashboard is a combination of worksheets. Story. A story can be a combination of worksheets and dashboards, and we will get to works with stories as well. That's a relatively new feature for tableau analysis. Just basically specifies how you want to um, do the analysis on the current sheet that you're working with. We will be working with this tab a little bit in the future. Map will work with this when we get to maps. Um, basically format. There are other ways to access formatting, and we'll be doing that in the course server. We won't be looking at server right now, and window help, these air just auxiliary functions. So then what we're going to look at now is basically, we won't talk about this right away, because we will get to know this ribbon as we progress the course. But right now, I would like to focus on the main working area where we will be creating a worksheet. Um, so here the main elements are columns and rows. So most of your work sheets will be created by deciding what goes into columns, what goes into rows. And then what goes into these other ailments, like what decides color would decide the size of your shapes. What decides what text is attached to shapes the level of detail. We will talk about aggregation more for the course and any tool tips that you want to put by. So the easiest way to explore is probably to, ah, explored by doing so. Let's drag a few things onto this worksheet. Um, I would assume, let's start, perhaps with region. So we just drag it into the middle here. And so we've put one dimension in and let's put another dimension, Let's say, um, units and right away you can see that by driving those two in a tableau has decided to put region automatically into Rose. Andi, um, your units into its sum them up. So it's aggregated them by region and its put them into a label. And so here you can see that now you can tell right away how many units were celled sold in each region. So now we can we can just drag and drop here. So if we're not happy with having units here, we can put them into columns, and right away we have a bar chart, and now we can extend this a bit and then reduces a bit. Now we can see by region. We can also see how many units have been sold, and you can also see that there is a tool tip popping up every time you hover over one of the bars. Now There's a very handy tool in tableaux, which is called Show Me Here, so I encourage you to play around with it. I don't normally use it in my work because, um, I already know what I want most of the time, but it gives you kind of suggestions and quick shortcuts to different things. So let's look at a pie chart. For instance, here now we can see a pie chart instead of Albar, Chet's. And now, if we want to increase the size, it's a bit small. Usually these pie charts so versatile will drag like that. And if we still not happy with the size this is bought, annoy here size to just click that and you'll see hard. Gross. Well, that's a bit too much. Um, so what does this show us? It shows us what region by color, has what proportion off the total sales and units. Once again, we're just playing around now where there's no intention of what for what we're doing. We're just exploring Tabal. So here you can see Central, um, East and West, and it's It's a prequel pie chart. But let's see what else we have so we can do a bubble chart right away. Tableau puts everything in the right positions for us. As you can see, there's nothing in columns and nothing and Rose. Everything's being put in here. Um, tableaux has selected circles for us from this drop down. It's created this bubble chart. So what else? Um, now that we can look at a tree chart tree map, that's what it's called treatment. So here. So it's like a bubble chart, but it's a bit different because it's got boxes instead off instead of circles and hear once again the relative size of the box. The area of the box is directly correlated to the number of units sold in that region. Um, you can just keep clicking around and you'll see different ah versions of the dashboard. That or the worksheet. That tableau is suggesting for you. And maybe you might be happier if one of them, but we won't rely on that. And we will create our own version, Um, in the next tutorial. So before we finish up, I just wanted to show you that in this show me, um, box. Some of the things are great out, and that's because you need certain, um, elements off daughter to create these. For instance, to create an area chart, you need a least one date. So zero or more dimensions, one more measures and at least one day because we don't have a date in our worksheet right now tableaux concrete and area chart for us. So if you want to add a date, you just drag a date in here and now it's highlighted. And now we can create a, um, area chart. But once again, we'll get to area charts, line charts and all of these other things for done the course. Today we're just exploring tableau. So look forward, seeing in the next tutorial, and until then, happy analyzing. 8. Creating Calculated Fields: Hello. This is Carol. And welcome back to the course and tableau. And today we will get to start sold in the problem that we have it had who gets a bonus. So we left off here, lost time. We were just playing around of tableau. I hope you had a chance to explore further. Ah, the different buttons and tools that temple has So for Because the more you player on with it, the better you get at it. Andi, it happens very quickly because tableau is very, very intuitive. Um and that's just we're talking just about the navigation. So, you know, basically where to look for what, right now, All share. Another cool feature is clear the dashboard. So we don't want any of this on DSO There's a button over here, the red one clear sheet. And so we're just gonna click that And what? Ah, everything is gone, by the way, if you're using the Mac or a Mac book, um, some of these layouts might be a bit different, so just kind of follow along, and you will be able to find where they are, but just bear in mind that they might not be in the same exact place as I'm showing. Okay. So Ah, let's start answering the question. Um, we were you know, that we can create bar charts, just create a bar chart for their representatives and see what the results. So we want representatives to be kind of in the columns. So there they are, our sales people. And let's see how many units each one of these representatives have. Soul has sold. There we go. So we can see that Richard has sold the most units, which is great. And how will, you know? Break it down by, um, region. So we know that we have three bonuses one for every single one off 14 the best representative in each region. And, ah, like this, we can't really tell who is the best in each of the regions. We could just tell who's the best overall. So what we're going to do is we're gonna take region, and we're going to drag it into columns. But we're going to put it before representative. So as you can see, I'm doing here, and I'm just gonna let go. And what does that do? Well, it gives us, um a kind of another level on top of all representatives. So first, the chart is broken down by regions so that you can see that here. So I'm just gonna make this a bit smaller so I can zoom in. So here you can see that the charges broken down central, east and west and then inside every region is broken down into, um by representative. And so that way, we can easily tell who's the best in sales in each of the regions. So here it's Alex here it's Richard. Here's James. And so no share Another cool feature. You can order these bars by their size. So if you see this little button here, so when you come roll over the access this this little button here. So if you click that automatically, they're sorted by size so you can see how drops off. And you think that this answers our question. But in reality, no, it doesn't, because units is actually the, um, number off items that has been sold. But as we know, our representatives are actually measured Ah, based on the dollar value of their sales. And so we need to find out the dollar value. But as as you can see here, there's no actual dollar value, total dollar value of sales. We know that, and it's really, really easy to find to see that because all of our numbers are kept in measures, so we don't have to look here. We can see here that we only have units and we only have unit price. And we have some of these other fields which we will talk about, um, further down, of course. But like the ones from our daughter, our units and unit price, there's no total dollar value. And that means that we have to create that total dull of value. How do we do that? Well, it's quite easy. You just have to multiply the number of units that representative representative had sold by the total unit price for those units. So if I click our daughter here, I go to view Donna, you can see here that Ah, when, for instance, Nick sold binders, he sold 29 binders at the price of $1.99 each. So the total revenue from that sale between you nine times one done $99 making it somewhere around $58 for that sale. So we need to calculate that multiplied value, and apparently it's not President daughter base, Moreno daughter said. So let's go ahead and do do this in tableau. And this is where we talk about creating calculated fields so you have to do is right. Click on measures, create calculated field, and we'll call it total Sales. And here we will call. We will take unit price or units and we will multiply units by unit price. It will click. OK, so now we have a total sales value. And as you can see, there's a little equal sign before the hashtag. That means it's a calculated field. So what we're going to do now is we're going to take total sales, and we will drag it onto a chart to replace the units. So I'll just drag it exactly on top. And as you can see, tableaux picks it up and aggregate sit, just as it did with units. Another way to do it is you can take this one off, remove it and then take total sales and put it on where you need it to be. And so now we have some total sales. And now if we order by, um, this value, you will see that we have a different picture now. Richard is no longer the best seller Overall. Susan beat him in the East region. Matthews the best in the central region, and James James is still the best in the West reach. So now we know who has deserved the bonus. It's Matthew, Susan and James, and that was an example of how to create a calculated feel in tableau. I hope you enjoyed that. And I look forward to seeing you next time when we will be talking about colors. Until then, happy analyzing. 9. Adding Colors: Hello. This is Curole and a warm welcome back to the course on tableau. Happy to see you here last time we left off after creating our first calculated field, which is total sales, and you can see it over here on the left. I just wanted to mention that creating calculated fields is a very important aspect or working of tableaux, because you will often find that the daughter that you have does not have the right level or does not have the right variables for you to work with. It does have the information there, but it's not in the right format. It's not, um, aggregated properly or correctly for your needs, where doesn't have the right level off detail or or other things, so you will be inevitably working a lot with calculated fields. And this was a very simple example of calculated field where we just multiply two realities . But tableau has very vast functionality in this space and allows you to create just insanely helpful, calculated fields, and we will be working with them going forward. So that's why I kind of put it at the beginning of the course, so you get used to it going. Azzawi get Go along. All right. So today we're talking about colors. Colors are important because, um, as you'll probably hear me say quite often, daughter science is not just about crunching numbers, its form off art. It's a form of communication. It's It's a very creative activity or profession. So, um, get get used to worker of colors. You will. You will need this skill. Okay, so let's get straight into it. How can we call this chart? Imagine that this picture has to go into a presentation for, ah, the executives of the company who will be distributing these bonuses. Or maybe even this picture will be, um, hung up somewhere on a wall so that everybody can see So you don't want it to be a plane like this. You wanted to be colorful and bright. Um, so we need to use this color button over here, and they are many different ways that we can do it. First of all, what we can do right away is just change the color. We can change it to read. We can change to green. We can change the basic of Anya color, and that's kind of the basic, um, thing that you can do here, Um, What? You can choose more colors and then you can choose. You can choose even more colors. It's it's old. It's all under control here. Um, what else you can do is you can change the transparency, but there's nothing behind it. So there's not much point you can add a border. Um, make that border thicker, I think, um, or make that change the color of the border if you want, but we won't be doing that right now as well what we want. We once kind of the colors to differ from bar to bar. So the first thing that you can do is you can take your representative on, let's say, from here and drag him onto the color. Ah, but And what that will do is we'll give each representative a unique color and we'll give you a color religion over here. And so as you can see, the color legend matches your column names. So Matthew is Blue Matthews blue here, Susan's Light Blue Seasons Light Blue here as well. Um, I wanted to show you a quick tip here as well. So by the way going forward, I'll be showing you quick tips along the way, which I will be using just because they're kind of a habit. And I think you should get into the habit of using them to. So, um, just keep track of when I give out these quick tips because they will be very helpful. So let's take out their representative. And instead of taking their presenter from here and dragging him onto the color Ah, what we can do is take represented from here whole hold him. As you know, if I just drag him into the call now, then it will screw up the visualization because now he's no longer or this column or this dimensions and longer in the columns. Someone's gonna press controls that now what you need to do is you hold him or hold this dimension. You drag him in your press control and is you can see this little plus sign appears under your mouse. And then when you let go, you basically copied that dimension onto this new role, and it's still in the cones. So that's an easy way, especially when you have, like, 100 100 or hundreds maybe too much like 30 or 40 dimensions here. It might be hard looking for it when you know exactly what you want. It's a radio on your charges. Just drag it like that with control. Um, okay, so we've got the representative here. I know. If we're not happy with the colors, we can just click colors, edit colors and choose a different color palette. So tableau has a lot of different kala pellets that already built in. Right now it's using tumbled 20. So you can say, how about we go for purple Great 12. You click assigned palette, and now it's a sign of purple gray palette. That looks pretty cool, doesn't it? Um, now we can. Ah, also another good one is color blind. So just to be caution of column of people who might be called blind, just click assigned Pelant there. It will tell you that Ah, your, uh, colors are being duplicated because you have less colors than, um, people. But, you know, that might be OK for you as long as you want, because you do have the names underneath, so it might not be a problem. Anyway, um, I don't think this is the best way to color this chart. Let's have a look, another one. So I'm going to I'm going to actually leave represented in color for now. At order we'll do is we'll take some of total sales, will press control, and we'll drag dad into color. As you can see, Representative has been replaced, and now some of total sales is dictating the color. And now it's It's not discreet color. It's ah, continues color. And so the more sales you've had, the darker your color, the last sales you've had, the latter your color, also quite useful. But in our case, it's not the best, because we already see the size of the bar, and it tells us how much sales each person has had. So maybe maybe a different approach. Um, my fared one in this particular case will be if I take region and I dragged region all into color. By the way, I'll just controls that, that you'll see that I can also drag region, control it and then replace this, um, current dimension that's in color, or not even to mention this is ah, measure. So replace that, and now you can see that you're bars have been colored by region, and I think personally, to me, this appeals the most because I can right away visually see that these of three distinct regions or three distinct elements on that kind of also, um, backs the idea behind why there's three bonuses and that these people don't have to be, um, compared to these people. And these people don't have to be compared to the rest of them. And so, personally, I would leave it at that. And that's Ah, how you work with colors in tableau. We will definitely be talking more about colors along the way. In this course, this is just the basics and have a play around with that, see what personally appeals to you the most, and it's you know, it's a very individual preference. So find find your style and I look forward to talking to next time when we'll be discussing labels and formatting, making our child look really appealing and until next time, happy analyzing 10. Adding Labels and Formatting: Hello, This is Curole and welcome back to the course on tableau. In the previous tutorial, we had a player around of colors and we had a look at three different approaches that we could take to coloring a bar chart. And we also discussed that coloring has a lot to do with personal preference because I might find something appealing. But you might not find the same approach appealing and vice versa. And therefore there is that element of creativity. And I do hope that you had a chance to play around of colors a bit more to kind of understand what you're leaning towards, what color palettes you prefer, what styles and approaches to coloring you injure more. But in any case, don't worry, because as we progress through this course, you will naturally start developing a unique approach to coloring to ah, formatting and adding labels. And, um, you know, creating your own unique visualizations and developing this unique ah style of visualization and ah, today let's move ahead and talk about labels and formatting. So we've got this chart in front of us, and as we discussed, there is a very high likelihood that this chart might, um, be featured in the report or be posted somewhere on the wall. So we want to make it look very Schmick and just very, very appealing to the eye. But that is not the only thing we're pursuing today. There is one more thing that we are after, and it might be it is definitely as important as making the shot look awesome on that is ease off. Understand? Let me demonstrate with an example what I mean. So here on this chart, we definitely have all the information that we need. We've got the names of the people. Ah, we've got the regions that they're working in. We even have the total values, um, off sales that they have performed. And this of the bars have this access. And you can, um, by looking the bar sell how much approximately each person has made in sales. So let's see what happens If, for instance, I ask somebody to tell me, um, how much sales has built made the person has to find Bill. So look around, then we find Bill here, then the person has to move their eyes up to the top over the chart and then the person has to. Don't worry about this. Pop up on the right here. It's just in tableau. So when you do produce this report, um, you won't have this pop up windows. So once again, the person has to find where Bill is, moved their eyes to the top of the bar and then move their eyes to the left to understand where, ah, the total sales it. And here they set about at about maybe 1000 there between 503,000. So maybe they said around 7 1050 or 1800 that's another one. Let's let's see how many sales James made. So once again, we find James remove our eyes top. Then we move our eyes to the left here, and we can see that James is somewhere between 1001 in 1500. But because he's further away from the axis, there's a bit more, um, room for error. So maybe he's with With this eye movement may be sitting at 1600 or 1700. We can't really tell. And so that means that the person who's, um reading this chart has to put in some efforts to get the information out of it, and that's not the way it should be. Tableau is a tool that allows you to very easily create visualizations, but also it has the capacity to make those visualizations to be very, very easy to understand. And that is an art form in its own. That is a part off what daughter scientists do. We look for ways to communicate information in very simple forms so that people don't have to put in effort to understand it and extract information visually from, ah, what we're presenting them. So let's try fix that. What can we do? Let's try adding a label. So here you can see this button over here label, um and what that does it adds textual information to the child. And what we're going to add is we're actually gonna take this. Some of total sales were gonna press, hold it, press control and drag it onto label. And as you can see here now, the actual some of total sales has appeared on the bar chart. Oh, actually, James was between 2500 so that's Yeah, definitely not. 1600. Um Ah, there you go. Now we can actually see the exact number off sales and each of these people has made. And, um, that already makes analysis or ah, reading this charred much, much easier. Now, while we're on the topic of labels, we can ADM or information to label. So let's say we want to add representative, just drag him into label. Now we have the name there as well. We can also drag region, but that's a bit excessive because we already have the representative name here, and we've got the region name here. And moreover, the region is the same for all these blue bars. The same free orange and eso That's that is definitely excessive. And we're just going to remove those now so we'll take region out and representative, And now we're left with the total number value of sales. Now you can edit the label further if you go into label and then you click this, ah dot dot dot button. Here. You can add your own text if you like, so you can say sales colon. Okay. And so here. Now you can see that your text has appeared in the label. Um, also, you can see that this label is not displaying any text because it is too big. It would overlap this label. And you can fix that by right clicking. Ah, and saying mark label always show, and that way it's always going to be displayed. Um, so now we're going to go back to label, go to the dot dot dot We're gonna take out this sales text, and we're gonna click. OK, so what we want to do now is we want to fix up the formatting of our chart and that ah, is probably the loss step to getting our chart to the ready for production level. So, um, let's start with the labels. If you want to change the ah size of the labels, um, you just go into label over here and you select size, uh, and you select a size size that suits you. So let's go with 12. And maybe you want to make him bold. Um, that looks pretty good. Also, if you go into dot, dot dot you can do the same here. So 12 and label size. Um, also, you can change the color. You can do a lot of things, but we will keep it at black for no. So that's good. That part's done. Um, another thing that we want to do is we want to change the type off label, and I'll explain what I mean now in a second. So we'll just right click on, um, the labels here. And so this is where you normally go to former things. Labels have their own formatting over here, but all other things in tableaux have formatting through this right click format button, which is pretty much the same as going here and selecting foreign tour. Um, other things like alignment and so on. So here in ah, when you right click and you go to format once again here, you can change. Um, let me close it again. So right, click format. Um, so this is the access You You've gotta be careful here. You've got to go to the pain because the label is in the pain, not on the axis. And here you can change the type of label. So just to prove that this is label, if I change this direction, you will see that the label is changing its direction Once again, you can do the same thing from here. You can change the alignment like that, which you condoms from. This from here is, Ah, the type off label and the type off numerical label that we're using. In this case, we're using numbers. So let's go ahead and change that to currency. Let's say we want dollars, so we'll go currency custom. Um, as you can see is automatically moved because it's not fitting but will take out two decimal points. And now you can see that this is much more, um, appealing. It's got the dollar sign in it. And now also, let's say we want in, um, units off thousands. So let's take a and we'll add one decimal point back, so that's even better. So now we can see approximately how much cells each person's made. It's very, very easy to digest. There's no, uh, numbers that you know that are unnecessary. One thing you should be aware of is you can't really change the form size through this menu Here. You see, I'm trying to change the phone size, but it's not changing. And that's, um, that's something just like a future of tableau that hasn't been looked at. That's because the label phone size actually overrides, um, the phone sizes just like here. So be careful of that. Okay, so we've formatted the label, know what else we're going to do is we're going to format the axis. So we're going to right, click on the axis once again, format. We're gonna go to access here, and we're going to change this to 12. So kind of his best to I keep the, um, sighs consistent throughout. Then we'll go to this axis will also quick format, and we'll change this to 12. Um, you can see that Matthew's not fitting in, so maybe make this a little bit bigger. No, Matthew fits in as well. Ah, format. This access changes to 12. Um, this is actually unnecessary because we know that Central means region. And we know that these people representative, so we'll just right click, and we will hide field labels and total sales. One more thing. So here, um, we will, right? Click edit access. Ah, well, split total sales by the two words, because that looks better. And also, one more thing in if we edit access on, not at Editori. We free format access and we go to access here. What we want to do is we want to make sure that these air also dollars so currency get rid of that. Make it K. And there we go. So no, it's it's consistent. You've got case here. Also you. It would be better to probably put one decimal place back because there is one decimal place throughout the charge. And that's how we for my charts in the next tutorial we will look at How do we how we can export this chart into other documents on duh look towards to you next time. Until then, happy analyzer. 11. Exporting your worksheet: Hello. This is Curole and a welcome back to the course on Tableau. And in today's tutorial, we will learn how to export our worksheets as images for other files. All right, so we've got this beautiful report that's ready to go. How do we put it into, um, a document, like a PowerPoint or a word document and so on. So one way is to take a snapshot. And, yeah, I knew a friend of mine, uh, he didn't know how to export, and he kept taking snapshots. So you just take, like, a print screen off this report, and then you stick it into, um, your file? Well, that that's not the proper way to do it. There is definitely a way to export files directly from tableaux. And, ah, today we're going to learn how so right away. Um, this is a worksheet, as we discussed, So if you're going to work shit and you go to export, you go to image, you can copy the image, so I'm just gonna close that because there's no way, another way of doing it a bit faster. You don't have to move. Um, also all the way up there uh, this is one of those tips and tricks. So if you right click and you go copy, you go image, you get the same menu. Um, so there's there's two ways to export. So we all we need right now is the view of the title on the college in. So we don't need the caption because we don't actually have a caption. We haven't created one for this chart. Um, we'll talk about captions further in the course there. They're pretty easy. So we'll take captured out on Bond. We'll talk about this menu in the second as well. So just copy. Now, let's bring up, um, the document. So let's say I want to export this image into a word document. So here I've got a word document prepared its annual bonus report, and I want to put the image in here. So what you need to do is obviously control V or just right click and paste. And there you go. So there's your, um, image here. So this underlying is because I had the underlining with her. So that's the image it blends in really well. But what do we see about this image that is right away. Not good. Wrong? Well, we see this name. We're here. So what went wrong? Why war did it come from? Let's go back to tableau and find out if I click on Tableau, You can see that there's no name here, but sheet one sounds familiar, doesn't it? That's the name of the tab here so that Ah, remember when we exported the image? So if we go toe right, click and then when we go to copy image here it says title and title is actually the name of the tab. So you either have to unclip title, which is change the name of the tab. And so let's do that. So I'll going to the name of the sheet. I'm going to, um, call it, um, annual bonus, um, analysis. And now, um, I want to see it here as well. So I'll go to work sheet and Old click show title. So here, Now we can see the annual bonus analysis name, and that also gives me the power to change and format. It's so if I click here and I click format title as you remember, our formatting pane pops up in the lift. And I can actually, um that sort of this, um, doesn't allow you to change the size of the text, So we're going to have to work on this a bit. You need to double click on the title to be able to form at the size of the text. In this case, it's 12. It's bold. So it's It's all right. It's the same as the rest that we have here. So just if you do need to change the former, that's how you do it. So I'll just click that, um and no, we can right Click, copy image. Um, view Title color legend. Copy. Now let's go back to our document. Delete that and paste in a report. Once again, this underlined should get rid of it. Okay, so here now you can see annual bonus report analysis at the top. Um, and that's good. So that's pretty much ready. Ready to go. You add some text for the executives, and it's ready to be presented. The only thing is, if you want a bit more space, So if you want to start a bit bigger than you want, region at the bottom and that way your child can expand to the right, and that's what we'll try to know so well, right, click right, click, copy, image and color religion. So but here will put the college in at the bottom, will choose that one. Go back here and paste. And as you can see, the collision is at the bottom and the chart has a bit more space. So that's the other way. You can do that. Um, so that's pretty much done. And so that sums it up for us for today. I just wanted to tell you that we still haven't saved a workbook, so make sure you do. So you go to file, save as and obviously you know, for for this workbook, it's section one. Just make sure you keep it saved because tableau doesn't actually all to save your work. And you want to keep it for yourself for the future. And that is it for this section. I hope you enjoyed it. Very, um, easy introduction to tableau. That was an easy daughter said. But it did help us get our head around a lot of things. And we talked about, um, navigating tableau, creating first calculate field adding colors, labels doing formatting. So all of that together, that's our base. We're gonna take that forward in the course. But before you do, proceed with the next lecture. Do not forget to do the quiz. It's right under this one. It will help you make sure that you've covered everything that we talked about in this section. I look forward to seeing you in the next section and until next time, happy analyzing. 12. Get The Viz: Hi, guys. I hope you enjoyed that section. And in this tutorial, I just wanted to show you that you can download all of the videos that we create in this course in order to get access to these visuals only have to do to bring up a browser and go to my tableau public profile. So go to www dot public dot tableau dot com slash profile slash curole dot Eremenko. And here you can see that you can download all of the visuals that we created this course and not just the pictures, but the actual workbook. So we have to do is select this download I can over here and you'll download the workbook to your computer, and you can open up in tableau so hopefully that will be useful. You can use these visuals to either check your work office. We've completed a section, or you can just download them before a section and follow along if you like. It's up to you how you'd like to structure this learning process, but these resource is out there to help you if you need them, and I hope that will be helpful. I look forward to seeing you next time, and until then, happy analyzing 13. Section 3: Intro: Hello and welcome back to the course and tableau. And I just wanted to congratulate you on completing the previous section. We did look at a very simple daughter said, But nevertheless we still learned quite a lot. You. So how you can create Joan Bar chart on how you can play around with colors and labels. We even got to create our very own first calculated field, which is a massive step. And we also so how we can export the results of our work from tableau into other programs. And no one will be doing in this section is we'll be looking at a very interesting daughter set, which is long term unemployment rates in the U. S. For the past couple of years, and we'll be looking to visualize how things change will be looking at trends and breaking them down by different categories and so on. And what we'll be doing, in essence, is will be working of time, Siri's daughter and will be visualizing it. And now, when it comes to Time series data in tableau, there's there's quite a lot of specifics that you need to know about, so I'll be definitely I'll definitely be sharing all of these secrets with you in one of the upcoming tutorials, and by the end of it you will know exactly how to work with Time Syria's Donna. Also in this section, you'll find a very important tutorial on granularity and aggregation, and those are the concepts that underpin the whole of tableaus work. So you do need to understand how granularity works and how level of detail works in tableau in order to be very good in visualizing things and kind of understanding exactly was going on behind the visuals that you're creating and so what you will learn in that tutorial you will be taking away throughout this whole course on through the rest of your work in tableau that you will ever be doing because that is just basically how this to work. So that's a very important to toil in. I urge you to pay attention when you're going through that one, because all the information you will need going forward Onda. Finally, we will look at some other things. For example, we look at filters and quick filters, which is another topic which will be taken away further down the course. We will create by the end of the story will create a beautiful area chart. And I'll show you how to format it on you. I'm sure you will be proud of which have created within this section. So I look forward to seeing you throughout this section. Andi, See on an X tutorial. Until then, happy analyzing. 14. Working with Data Extracts in Tableau: Hello and welcome back to the course and tableau. And today we will be looking at the data set for this section of the course. So let's get straight to it. We're going to need a browser, and here we're going to go to super dot whoops, data science dot com slash tableaux. And now we're going to scroll down, find section three. Ah, so we're looking at times serious aggregation and filters. Who? Interesting. Okay, so long term unemployment statistics. That's right. Click Save link. As as we usually do into our folder, I'm gonna bring that folder up tableaux course. There it is. Long term unemployed statistics. And let's open up and have a look on once again if, um if you are, if you don't have Microsoft Excel, then feel free to install open office. It's a free piece of software which works on both Windows and Mac, and you'll be able to view these files there. OK, so as you can see, the format of the file is very different to I'm just gonna zoom in a bit to what we saw in the previous section. So here we have, um, a lot off like duplicate records in each on and many of the column. So, for instance, ah, the period here for, um, the periods repeated. So here we've got January many times and we've got february many times March many times, Then we've got the gender. So for January, we've got six eyes a nose 71234567 rows for men and centros for women. And then the same thing happens for February 7 and seven and so on. And then for men, we have the split into the age group 16 to 1920 24 so on. And all the way up to 65 years and over And then for each one of these rows we've got And, um, a number off unemployed people s o in that age group off that gender in that period of time . And so this is a very non human, like way to structure. Donna, Um, it's not something that, like you, you would expect to see if you were given a list. Ah, a an Excel spreadsheet to just look at It's not how you ah, taken information very quickly and efficiently. So what's humans are more used to is looks a bit different, and it wouldn't have all these duplicate records. It would. Look, this is kind of a pivoted view as humans. We're more used to unpick interviews, and I've got an example of that switch I'm just gonna bring up now so that we can compare. So tell me if this looks a bit better, So here you can see age. So the groups age groups, and then you've got the year and they've got men and women. So if you need to look something up, you're gonna quickly. Okay, So if I need March 2005 men in the age 40 25 March 2005 men aged 40 25 There, there so is easy. Is that, um and it's kind of more natural for people to look at this, But for machines for computers, it's more national to look at this because they know exactly where to find everything. And it's just, um, foster. And it is just more of a machine formats. So this daughter is already structured in this format, which is going to be easy to import into tableau. So this is easy. This is gonna be would be much harder to important to tableau. But don't worry. We are not going to focus on that right now. We will talk about structuring and preparing your daughter in a separate section of this course is it's a massive topic and we're gonna devote a whole section to it so we'll do that further down in this course. But for now, let's just work with this daughter said that we have here, which is smaller unemployment daughter. So we've downloaded that lets clothes, the's spreadsheets That's open up tableau. There we go. And here you can see how previous to workbooks that we worked on. So let's connect all daughter source. Let's go to excel. Ah, long term unemployment statistics Open up and there we go. So it's in sheet one and there's a preview of all data. Looks good. What we're going to do now is we're just going to goto work book. So we've actually connected to the daughter. There it is. However, now I will show you one more thing. I knew a new element to working of daughter, and that is working with extracts. So you see this bottom here you can actually connect to this daughter, but extracted right away. So also, you can do that while you're in the world book and you can do it from the worksheet, and we're going to do that. So moved back to your work shade without, you know, doing any kind of creating in dashboards. Um, just right. Click on the daughter and go to extract data. And so what this does is it creates an extract for tableau to work from. So basically, instead of connecting live to daughter, the daughter is going to be extracted into a separate file and then is gonna be kept there . So we're gonna click extract. And here you can choose where to save this file, going to save it in the same folder click Save. And now you can see that the Aiken has changed. Is got this little arrow, And if you right click, it says use extract. Now, if we go to the folder, which is here, you can see that there's a new file that has been created sheet one long term unemployment statistics. So this is the extract. So our daughter from here is now being kept in here, so there's like a copy of the daughter. And, um, if you open up, you won't see anything. Basically, because it's a tableau. Ah, table four months and keeps it in some way. Um, so what happens now is if you change anything in this file in the file that we originally connected to, then nothing will change in your workbook. So if you change the daughter, you will still have the old daughter in your extract. So it might be a good thing. Might be a bad thing. If you don't want your daughter to change after you've connected for the first time, then it's a good thing If you want to keep your daughter updated to the original data source, which doesn't have to be an Excel spreadsheet. Could be a database. Could be a CSP file. Could be anything. Um, then you can do that as well, so you go to tableau and right click. Here you click extract and you refresh and then here gives you a question. You say yes, and your daughter's refreshed. So why would you use extracts? Well, it's quite simple. We're still working with small daughter sets, but when you start working with big data sets or dynamic daughter says that often change. Um, using the life connection might be slow, and it might not be reliable. It might. It might be constantly changing might be hard to work with, So that's when you create an extract. You do your work, and then you decide whether you need to return to the life connection or keep working with the extract. And if you want to return to life connection, you can always do that just right. Click and uncheck use extract and the right away you can see. Now we're using the normal connection again, and that's how you work with extracts and tableau. So for us in this particular example doesn't matter. We're just going to keep using the extract because our daughter is not going to be changing . We don't really mind. What we're going to be using are going forward in this tutorial, and that's all for today. I look forward to seeing you next time when we will be looking at working with time, Siri's. Until then, happy analyzing 15. Working With Time Series: Hello and welcome back to the course and tableau. In today's tutorial, we will learn how to work with Times Series daughter. But first things first. Let's go ahead and save a workbook. We've already connected the daughter source, and saving a workbook will prevent from loss of any progress that we make along the way in this section. So let's click, Save as and give a workbook. A name in this case will be Section three for me. Click, Save and now it's saved. And all we have to do when we make changes is just press control s on the keyboard and that'll save our progress. All right, so now we're trying to visualize times he's done. Let's have a look at our daughter first and understand what we're working with. So if we're right, click on the daughter Source. Click view daughter. Um, you'll see that as we discuss, we've got ah, age, gender. So two categories. Then we've got period and we've got an unemployment value for a TRO, and that's exactly what we want to visualize. We want to see how unemployment is changing as period changes. So we scroll down, we can see that we have many months. We've got a month for every single year or we got 12 months for every single year and we can see how unemployment is changing. So we want to visualize that. So let's go ahead and do that. What we're going to do is we're just going to double click on unemployed, and then we're going to double click on period. And she see how tableau is very smart there. It's automatically put unemployed into, um, Rose, and it's summed it up and it's put year or it's put period into columns and steak in the year of the period. So what's going on here is there's some aggregation on. We'll talk about aggregation Mawr in the next tutorial, but, ah, it kind of makes sense already. What is happening is Tableau is taking a lot of the daughter that it can see, say, 4007 and and it's summing it up a lot of the values in all of the rows that have 2007 in them. It re irrespective off month off, gender, off ages, just summing him up and coming up with one single value 4007 then the same thing for 8 4009 and so on. So that will make sense. But now we've kind of got a bit of ah ah, question here. Ah, we know that our daughter has much is much more granular than that. We know that we have year months in every year. Ah, and we have information for that. Where? How do we get to that level of granularity? Well, let's and go ahead and explore that. If we go to the, um the drop down here, which you can see for this dimension and we click it, you'll see that there's two sections in China which are responsible for time. There's this section which has year, quarter, month, day. And then there's this section, which also has year, quarter, month, week, number and day. What's the difference between the two? Well, just to find that out, let's click on month in the first section and right away you can see how we no longer have years at the bottom. Instead of that we have instead of that, we have months and what happened there? Well, the other thing that we can also see is that, um, we have only 1 January on only 1 February and only 1 June. We know that in our daughter we have many Junes and many February's. We have one. In fact, we have one for every single year. But, um, in this case, we're only presented with one of each months, so we only have 12 points on this chart. And what is going on? Well, what is happening is Tableau is taking all of the daughter from our data source, which has the say, for instance, may for any any row that has may in it. It will take it and aggregate it to this value so it will add them up, irrespective of age, gender and even year. And for that, for us, that doesn't make any sense. What's the point of adding up unemployment for 56 6007 and so on Come out for a number, that number has no meaning to us as a wise, that help happening Well, the reason is is because in this case, tableau is recognizing recognizing month as a dimension. And how can we tell that will Tabler is giving us a hint up here. You can see that month off period is being highlighted in blue, So tableau always Hal Ides dimensions in blue and measures and green. And so that tells us that table is recognizing this new variable because, in essence, it is in your variable. Ah, with our variable in the daughter sources called period, we don't have appear. We don't have a variable that is called month, but tableau is creating a calculation here, Um, and you can double click on it and see what the formula is. Um, so tableau is creating a calculation, which is month off, period. And, in essence, that's a new variable and tableaus recognizing this new variable as a dimension and that means it will treat it just as it would treat age are stories just as it would treat gender or, in our case, age because we have aged groups. But let's let's think of it is engender. So Tablet is treating this new variable as a categorical variable. It only has 12 categories, and it's putting the daughter into those categories. Well, obviously, in this case, we don't want that we don't want, um, different categories of months. We actually want a timeline over here at the bottom. So how do we get that? Well, instead of this month, let's go ahead and select the second month over here in this drop down and right away, you can see that all chart changed. And also you can see that now, Um, month off period is green, So this variable this time is being recognized as a measure. So if it were a calculated variable, it would be sitting over here. And what then happens now is that we have a timeline at the bottom and we have all of the months. Ah, with all of the daughter that we're looking for and this is exactly what we wanted. Um, so just to see the difference, let's click again and will select year instead of month. So here you can see a similar charge to what we had before, so I'll just bring that on up here. You can see very similar line, but here you've got categories of years. But if we click this year at the bottom here, then here you've got instead of categories of years, you've got a timeline. And the only difference with the month timeline is that there's less dots on this timeline . And in fact, you can see the daughter few in line. If you click on color and you select this option, you'll actually see the dots here. So you have less dots on this timeline. Ah, and all we're doing by changing this level here is we're changing the granularity off this specific timeline. So we're just saying we want more dots on the timeline. We're not changing the category that we're grouping observations into. We're changing the granularity off are tan line on the number off ticks on the timeline. And if we change month, there we go. So we're also once again we're changing, um, the granular granularity, although timeline, so I'll just change is back to normal. And that's exactly what we want. So you have to be careful off that, And that's an important part of Worker of Time, Syria's daughter, that you need to understand what you want from your time daughter, whether you wanted to be a dimension or a category, or whether you want it to be a measure. In this case, we wanted obviously to be a measure so we can plot a timeline like this. And so That's pretty much it for today. But before we go, what I wanted to do is I wanted Teoh show you how you can validate this chart. So this is unemployment, daughter for the U. S. And obviously it's publicly available, so you can just go to Google and look for unemployment. And 27 weeks is long term unemployment. We're looking at long term unemployment 27 weeks and then just type in Fred Fred stands for ah, Federal Reserve Bank of ST Louis. So if you go here, you'll see a very similar chart and Well, um, here I can change it to 2005 so you can see that looks a lot like our chart. Um, the only question we've got We can just look at the tip here and see 6800. And in our chart, it's 7100 or 7,100,000. So Ah, it's of course, you'll have a bit over a discrepancy if you have daughter from different daughter. Sources in this case is about 300,000. But the way ah, like e look at it. If it's statistical daughter, so is 300,000 and you divided over 6800. So that's less than 5% difference. And, ah, for what we're doing for our purposes, that will be sufficient. Level off precision and you can see the charts are quite similar. So we are working with actual unemployment daughter in the US for this period of time. Okay, so that's us for today. And next time we will be talking about aggregation, granularity and level of detail. So I look forward to seeing in the next tutorial will be a very important one. And until then, happy analyzing. 16. Understanding Aggregation, Granularity, and Level of Detail: Hello and welcome back to the course on Tableau. And today we're talking about aggregations and granularity is gonna be a quite an important tutorial because the things that you learn today, you will take away and apply throughout this course and throughout all of your work of tableaux, because these things govern how tableau operates. So let's get straight into it. Here. We've got the chart and the charter we've created, and it's sharing us unemployment in the U. S. Ah, month to month from 1005 2015. Now, the question that we have is how does tableau know that we want to see it at the monthly level? How does table know that this aggregation that is doing summing up the unemployed variable How does it know that we want to see it at the month level? How does it know that it needs to sum it up at the month level? So the answer is quite simple. Tableau will always aggregate measures at the level off granularity off your worksheet. So in this case, because we have this variable here, month of period tableau knows that we are intending to see all of this daughter there were plotting at the level off one month or at the granularity over a month. And so what? That means it was. If I remove this, if I just drag it out of the dashboard or the worksheet, you will see one single dot. So instead off, um, lots of daughter line tableau has no now tabla has no clue at which level of granularity we want to see the worksheet, and it assumes that we just want to see it at the broadest level possible, and that is at the level of the whole, Daughter said. So what it does is just sums up all of the, um values for this variable unemployed into one single value, and it puts it for you. So I'm just going to control Zed and return month of period. And so that in this case, month of period is a variable that governs granularity. Normally, what happens, or quite like the concept behind tabloids that measures get aggregated and dimensions specify the level of granularity, and we'll see how that works in a second in this case, month of period. Even though it's recognizes a measure and it's green, it is still the variable that is specifying the level of granularity. And that's because it introduces this axis or a timeline the bottom. And it actually specifies that we want to see it at the monthly level. So it makes sense for tableau to assume that we want to see this chart at the level off granularity of a month. So know what we can do to ultra go. Segregation is we can go to announce, and we can actually switch it off. So if you just uncheck this box, you'll see that you get this fuzzy chart. And now we're just going to replace it. Um, with a shaped charge is to make it look better. And you will see that now, instead of aggregating the Donna tablets just plotting unemployed. So basically it's planning every single row off our data set separately on this chart, so you're gonna have a lot of values for the same month in the same year. And B, That's because we have two genders and we have a lot of different age groups, and now if we look at the bottom, we will see that there is a total of 1708 marks, and that is Ah, the total number of rows that, um, we have in our daughter because our daughters at monthly level. So if we go back to, um, our ah, plus here we're just going to switch aggregation back on and I'll show you another way we can alter aggregation. Um, Now, what we can do is instead off switch aggregation off. We can introduce a dimension which will change the level of granularity or dashboard, and therefore it will affect the aggregation. So we're going to take gender, and we're going to drag it onto color, and right away you can see here that we have twice as many adults. Um, the blue dots represent male, and the orange dots represent female unemployment for that specific month. And now Tableau knows that because we have this variable here, which is month of period, and because we have this dimension in a worksheet, it knows that we want to see everything, or we want to see all of the measures aggregated at the level off granularity off month plus gender. So if we look down here, you'll see it. This 244 marks, that is Ah, twice as many um, marks as we had when we had, um, months. I'll just take a gender out for a second and you'll see that we have 100 22 marks. And so now, if we return gender back into color, there's 244 marks, and that is telling us that the level of granularity has become even ah, smaller or bigger, actually. So we the chart has become more granular because we've introduced this dimension. What else can we do? We can introduce mawr dimensions to increase granularity even further, so let's take a judge and drag it into shape. So now you can see many more marks and you still see orange and blue Orange represents. Ah, gender and blue order represents female and blue represent male, but at the same time, there's different shapes on the chart. Now they're circles and squares is crosses. There's pluses is lots of different types of shapes, and its shape represents a different um group or a different level kind of a different daughter point or a different point on our chart. And, um, Tabal knows the level we want to aggregate at because it can. Ciel the dimensions on a worksheet, you can see that we have gender. We can would have age. We have, ah, month of period. So it knows that this sum is known now has to be calculated having these, um, this level of granular granularity in mind. So that's how aggregate That's how granularity works and aggregation works together of granularity, credit clarity. Let's have a look at different types of aggregations that are available, so I'm just going to remove age so it's not too cluttered. And now what we're going to look at is not some of unemployed were actually going to change it. And if you click this drop down and go down to measure some here, you can change what you want to see. So let's say you want to see the average unemployment for that month. If you click that, you'll see the chart didn't change much. But the axis actually change. So when you had some, it was a total unemployment for that gender for that month. Now, if you click measure average, you will see that it is the average unemployment for that gender for that month. This is another one. Let's look at same median. See, now the chart changes because it's actually showing us, uh, and the access changes as well. Um, but now it's not proportional because it's medium. And now we can see that these marks air presenting the medium median unemployment at the level of granularity off this worksheet, and that level of granularity is month plus gender. And so, basically, that's how granularity and aggregation work. The only one more thing that I wanted to show you, and this is important is detail, so sometimes you might want to increase your level of granularity. You want to make your dashboard mawr detailed or more granular, but you don't want to drag anything on to, um, your like color or shape. You don't want to affect the visual. Ah, like coloring or other parts of your desperate. But you do want to increase the level of granularity. Well, tableau has a solution for that. There is this option. Detail in detail doesn't actually mean like, um, detail, as in words or description. It actually means that level of granularity of your chart. And so let's do that. Let's take a judge, and instead of dragging it on to shape like we had lost them. Let's put it onto details. What happens now? You can see that the shapes haven't changed, but the granularity off the chart has changed. So basically, um, this is an option for you to add dimensions and measures to your dashboard without actually affecting the visual representation, but affecting the level of granularity. And that's exactly why this, but in detail or this Ah, um, option detail is here. It's for you to control at which level of aggregation is going to happen. So just remember about that because, ah, we will be using that going further in the course. And you will definitely, um, find it helpful and handy when you're doing your own projects for work or at home. So that's all for today. I hope that was helpful. And let me know if you have any questions whatsoever, because these are important topics that we will need going forward. And in the next tutorial, we will start creating this awesome looking dashboard for unemployment worksheet for employees work. Shit. Dashboards will come later. All right. I look forward to see you next time. And until then, happy analyzing 17. Creating an Area Chart and Learning about Highlighting: Hello and welcome back to the course on tableau, and in today's tutorial, we will learn how to create an area chart. And also I will show you a cool feature which you can use in your daughter discovery processes. So we'll start off of the feature right away in front of us. Here. We've got the charter we created Lost time, and by no means is this a final product and con going to any report, and it's way too cluttered to present any inside full information. But at the same time, you might find yourself with a chart like this or something similar. While you're doing your daughter discovery process. While you're looking for those anomalies trends and patterns, you sometimes we'll find yourself a very, very clutter chart. Wish you are trying to interrogate to find those answers. So here what we have is the representation off unemployment, long term unemployment in the US between 2005 and 2015. So we've got this timeline here. It is shown to us by month. It is the median over the unemployment, and the granularity level is gender plus age. So that means for every month there is several age groups, seven age groups, times two genders. So for every month there's 14 observations that are presented in this chart. And as you can see from the color legend here, men are represented in blue circles and women are presented with orange circles. So what happens if you want to interrogate one of these genders, mawr specifically, and understand exactly what's happening there? Well, one ways to restructure the chart and just leave that one gender. But there's another great approach, which is called Highlighting, which helps you achieve the same result but much foster. And all you have to do is go to your color legend and just click on the gender that you're interested in. So if you're interested in looking at women, it just click on women. And there you go. So that that is representation off female unemployment for that same period for those same age groups and also same thing you can do with male. Just click on men and you will see that the circles associated with male unemployment are highlighted for you right away, and a lot of people forget or don't even know about this feature, and therefore they spend too much time restructuring their charts. But in reality, if you just doing data discovery and you just want those answers quickly and you want to understand exactly what's happening, it's a very handy thing to know and to have. So, um, definitely look into that Well, I'll just share another example. Now let's look at age. For instance. We know that we have Asian, the chart as a level of granularity, and we the way we got it there is. We dragged it into the detail shelf so it is, um, increasing or making the charm of granular. But at the same time, it's not represented anywhere on the chart. It's not a color, it's not a shape. It's nowhere. So if we want to be able to highlight age, we need to give it some sort of representation visual, or is a presentation on a chart. And so because colors are used, let's drag age into shape right away. You can see that now, for every single age group Ah that we have. We've got a new shape and we would want to highlight, say, 35 to 44 years old, and we would press here naturally, but nothing happens. So as we click around, nothing happens. Nothing's being Holland, but that could be easily fixed. You just have to go to this. But annoy here, which says highlights selected items. And if you click on that now, it will allow you to use this legend to highlight the items that you're interested in. And as we click through, you can see that we're focusing on the different unemployment's off different age groups. So once again, very handy feature to nobody and to use in your daughter Discovery definitely take it into your daughter. Science Arsenal. All right, so what we're going to do now is we're going to create an area charge. Let's ah, move back to just our original line charts. I'm gonna take age and gender out, gonna change this to line. And instead of media unemployment, we're going to look at the sum of unemployment. So now we're seeing the total unemployment or long term unemployment for every single month in the U. S. Between 2005 in 2015 so the child ranges from 0 1,000,000 to 7 million. Eso no, What we're going to do is we're going to take age. So the age groups and will drag it into color. And what that will do is it will give us many line charts. Now the charred ranges from 0 to 1.6 million, and every single line charge or line is here is independent. And so, for instance, um, like here, you can see that for 35 to 44 years old people in April 2010 that employment is 1.38 million, and once again we can use the college in to highlight the lives that we want to look at. So that's handy. But at the same time, this visual is not very useful. You can. It's not easy to understand. And as we discussed it is our job as data scientists to make these visualizations very friendly and very easy to interrogate for people who are looking at them. So what we're going to do now is we're going to change this visualization to a different type, and one way of doing it is just trying to explore and finding out what visualizations going toe work in this particular case. So for that, you can use this show me function and you can just click around. So, for instance, you look at a tree map is a tree map going to work and right away you can see that even though it looks bright, quite hypothesizing is not gonna work for a report. It's not. You can't really tell much from this. Ah, utilization. How about a, um, bubble chart? Once again, very beautiful. In terms of arts, this is probably a 10 out of 10 But in terms off, inside, fullness not really can't really tell much from here. Too much information being thrown at me. Um, so you can just click around and find the best one that you like, but the one I suggest going with in this case is an area chart. So we're going to click on that, and right away you can see how this area child has Bean created for us, and it looks pretty incredible. Andi, Very, I think insightful. And we'll learn how to, um, make it even better just now. But before we do, what I'm going to do is I'm going to show you how to create it from scratch without this show me. But it so I'm just gonna cancel Close that, and I'm just gonna cancel these steps and go back to a line chart. So what you want to do here is if you go to the drop down here instead of line, just go to area and what you'll see is now all of these unemployment rates have bean ah, stacked on top of each other. So look at this axis here. I'll just go back to the line chart. So I'm just gonna click here. You can see here that it's only goes up to 1.6 million, and that's because each one of these lines is independent. Now, if I go to area, it goes all the way up to seven million now that's because they're being stacked up. And as they're stacked, the total increases here as well. So the the actual unemployment for different groups, different age groups, is given by this pop up over here. So, for instance, in this case is 1.56 million unemployment in that month for 25 to 34 year olds. So that's how you create an area chart. And once again, you can still highlight with color. So remember about that. That's a very powerful feature, and what else we can do here is we probably can add some labels to make it really a little critical. So we're going to take a judge, press control and will drag it into label. And now you can see that the label has been added and once again we can. As we know already, we conform at these labels. Um, maybe make it bold. And as you can see, this is already starting to look much, much better. Ah, there's no label for the top one. That's because it probably just doesn't fit. But it kind of makes sense there, Elin like ascending order going downwards. And so that sums it up for us. For today we learned how to create an area chart, and we learned about highlighting. In the next tutorial, I will show you how to create a filter. We will use gender as a filter, and I will show you also will recap a little bit on a level of detail and granularity and highlighting as well. So I look forward to seeing you next time, and until then, happy analyzing 18. Adding a Filter and Quick Filter: Hello and welcome back to the course on Tableau. And today we're looking at filters Important lecture today. But before we get to a one and toss you for a favor, so why, No, we're not finished with the course yet, but I would really appreciate if you could leave a review for this course were. We've done a few modules so far, and if you like the materials, please go ahead and click the bottom of the top of the course, which looks like this. And just choose the number of stars that you think the course deserves and leave a review if you like. If you If you don't want to write anything, just choose the number of stars and click submit. Um, the reason I'm asking now is because a lot of students don't finish the course to the end for whatever reason. And I definitely hope is that you're not going to be that student. I hope you get to the end. But at the same time, I would really appreciate a review because it helps me understand whether you like the course or not, and also helps other students who are considering taking this course understand whether it's where if they're well, so I would be very happy if you could do that for me today. And now let's get back to the show. So we're talking about filters today. We've got this area chart that we created last time, which, if you ask me, looks pretty amazing already. We're just going to add a bit off formatting to it at the end of this lecture. But how can we add a filter? So what information is missing? Currently on the start, the information is missing is gender. We've got the age groups, and we've got the unemployment rate split by months. But we can't see gender here, So one way to add gender is by putting gender into a fielder, and that's exactly what we're going to do. So to do that, you have to take gender, or or the variable that you want to add a filter and put it into the filter shelf. And it's a simple is that There we go. So now you've got this filter. You mean you pop up and you can, um, specify the kind of settings or set up your filter. So here we're going to select. We're allowing, um, this filter to work by selection from a list. And there's only two values men and women. Um, custom value list. I don't normally use that. You could add, like your own types of values use all. So normally you stick with this select from list, and this is for, like, dimensions. We'll see. We'll look at a filter for measures in a in a second. So, um, wildcard. Usually I don't use any of these is a more, um, advanced kind of things that you use in very specific cases. So we won't stop on them right now because if you really need them, you can understand them. But to be honest with you, I very rarely I don't think I've ever used the wild cards in my filters. That's when you have, like, huge lists that you're filtering from, so we'll just stick with general and for now, we'll just select all. And the other thing that you need to know here is you can select exclude, and what that will do is it will allow you to filter what you don't want to see. So if you have like 10 values, then you could click exclude, and that will allow you to cancel out a few values. But right now we're just going to select what we do want to see so we'll click all. We'll click. OK, and now you can see the charge in change because we select both genders. But now we have gender is a filter. And so if I want to change the filter, I click filter and say I want to see the child only for men. Then I click. OK, then you could see the chart did change because now it's only unemployment for men and the access is much, um, the top value or the Maximilian X is much smaller because there is less, ah, unemployed people because we're only looking at a subset now if we want to change it for women, you uncheck that and check the magical comply. You see the child is changing in the back there, so that's all great. But that is quite tedious. Don't you find like you have to click the field to every time and then change it and close it again? So that's why, in tableau there is a solution. There's a quick filter and We're going to learn that right now as well. So in order to bring up a quick filter, you need to, um right click on the filter and select show quick filter and just click that and you will see this quick filter pop up over here. So it's quite far away. Um, how about I just put it there so I will put it there for now, But usually you keep it on the left. I'll put it there just for our convenience so I can zoom in a bit. And so here, if I uncheck men, you can see the chart is changing right away and check Women. Chart is changing so I can take all of them out. The charge disappears. Very handy thing to have this quick filter because it helps you quickly analyze your daughter. You can change it toe type of quick field. So you want to see and you can look, um, you can see these different types so it could be a drop down single slider. So what we're going to do is we're going to actually put this one back here, and now I'll bring up a quick filter. So actually What I'll do is I'll make my tableau workbook smaller so we can zoom in like that. There we go. So now what we're going to do is we're going to add a filter for age because there's a lot more values. We have an edge and that'll be a bit handy. So let's just do that. Will put Asian to filter, will select all for now, apply, and we'll also create a quick filter for age. There we go. So that's how quick filter for age. And now you can see, um, how we can customize this filter. So first of all, we can uncheck certain values, and as you can see, they will disappear from the chart. So this is not the best thing to have for this chart because we do want all groups off ages in unemployment in this chart. But we're just looking at it like this for now because it's a good example. So, you see, we can uncheck the valleys we don't want to see in the chart changes right away dynamically right in front of us. Um, so then we can just select separate ones, But once again, there's that option to highlight, so you wouldn't need to do that ever. If you have this highlighting option and then next, What we're going to do is we're going to look at the types off filters you can have so say you can have a single valueless. If you only want to see one at a time, then you can just, ah, do these radio boxes and also have this all option. Also with filters, you have the option to, um, remove this old value so I can un check. And then there's no old value, so you have to select an option from the list. But in our case, reaction need the old value. Um, so how about we? We can also have, like, a single value drop down, so it's like a radio books, but it's a drop down. It's a bit more convenient. Um, what else? Um, you can do like multiple values drop down so you can check them so it just kind of makes compact. You can do a wildcard match where you type in 20 to 24. Let's see that and will pick up the value that you're looking for. So there's a lot of different options for filters and the more for convenience. Um, so that's that's pretty much that. I'm just gonna get rid of this one because we don't need ages of filter. The other one I want to show you is, um, we'll probably have a look mawr at measures as filters in the next section because it will be more relevant there. So, um, we'll definitely have will definitely look at that in a bit more detail. But just so that you know, you can, um, add filters and there be very easy to use. So in this case, if somebody wants to analyze only men a woman he can select from here. So actually, I'm just going to change this to a single value flown from list, and that makes more sense. So you're either looking at everybody. Are you looking just men or just women on the chart adjusted dynamically. And you can just look at exactly what you want to see. So, as promised, we're just gonna quickly fix up the formatting here so we'll just go formats and make it like a 12 on a B unemployed, and then we'll change for my right here as well make it a 12 and be on and make this a bit bigger. Um, so there you go. There's a chart. It's ready for export. If you really want. You can add some text over here just to replace this label. That's Ah, missing. But otherwise I think it looks probably quite good. And, yeah, so that's all for this section. Hope you enjoyed creating this charred. We learned quite a lot of new things on DA. Make sure to do the quiz because that will help you solidify your knowledge and to finish off. I just wanted to remind you I would really appreciate if you could leave a review. That would mean so much to me. Thanks a lot for watching, and I look forward to seeing you in the next section until next time. Happy analyzing 19. Section 4: Intro: Hello and welcome back to the course and tableau. How did you go over the period section? Did you find it fun working with the time series daughter and creating that are cool area chart? I would really like to know what you think. So if you have any comments authorities making definitely leave them in the discussion sections off this course. Otherwise, what we're doing in this section is we're looking at maps and scatter plots, so we'll be analyzing the data or sales daughter of a certain store in Europe and will be creating a huge map off how it's performing across different regions. And we'll also have a scatter plot for the customers. So you'll learn. You'll definitely know how to do those two things. But probably the most exciting part of this section is that we will finally get to create a very first dashboard. So so far we've been working with worksheets all the time. Now we'll be creating a dashboard, and we're dragging the map in the scatter plot together, and we'll be think we'll even see how to create actions. So make the dashboard interacting interactive so that you know you can click on different parts of the dashboard and adjustment. No, actually, start exploring all of this. All of these powerful features of tableaux. So exciting section ahead. And I look forward to seeing it throughout these tutorials. Until then, happy analyzing. 20. Joining Data in Tableau: Hello and welcome back to the course on tableau. And in today's tutorial, we will download and connect to the daughter that will be working within this section, and we will also learn how to do it. Join in Tableau. So very interesting to trial ahead. Let's get straight to it. First of all, we'll need a browser, and, as usual, we will go to Super DOT assigns that calm slash tableau. And here if you scroll down to Section four, you will see maps and scatter plots. And let's just download this file, which is amazing Mart you. So I'm going to say that filed to my tableau folder now, and once a file is saved, I can open up the folder here, you see the file and let's open it up and have a look What's inside? So there's my file, and I'll just zoom in a little bit so we can see a bit better what's going on. And here you can see the first thing that pops into um, our attention is that there's three taps, list of orders, order breakdown and sales targets. So right now we're looking at the very first step. What is it showing us? Well, this tab is showing us a list of orders. So, um, these orders this column of the values in this column are unique. Um, and every single order. It has its details here on the right. So when the order was placed, who the custom is customer is What's the name of the customer that placed the order? Which region of Europe? The order was placed in which country? In this region which state? In the country which city? In the state. And it also has information on whether this customer shopping as a consumer, a corporate customer or whole, or for a home office has got the shipping date and the shipping mode. So basically, every single order is described here in detail on every single order is only featured ones in this tab, and that's an important observation. Now, if we move on to the second tab, we will see order breakdown. So this stab is different Now. Here we can see that some orders are duplicated. For instance, these two orders are duplicated, so it's the same order, but it's shown twice. Well, why is that? And that is because the customer that place disorder actually ordered several items. He ordered Boston markers and Elden folders. And then, for each item there's a discount, the value that was discounted off the order. Ah, the sales the prophet follow for that specific, um, item the quantity. The what category falls under, whether it's office supplies. Ah, furniture or technology and the subcategory. So here we can see that every single order is broken down. It is itemized into what exactly constitutes that order. So we don't We no longer have information on with when the order was placed, which regions was shipped into. But we know what was inside this order. And so if we go back to the first tab here, we will see that in total, um, at the bottom. So if I just highlight the school column, you'll see here that there's a Collins of 4118 cells. So basically, because the first cell is the header, there's 4117 orders. And in order breakdown, as we can expect, there's Mawr cells. There's actually 8000 and 48 cells, so that means 8000 and 47 items in total. Ah, were well constituted these orders that were made. And so that's important to remember that in this tab order ideas unique in this tab board I . D is not unique animal. And finally, there's another tab called sales targets. Now, in this section of the course, we won't focus on the sales time and targets tab. We'll talk about it in the next section, so let's leave it for now. What we will need in our data is we will need to somehow join these two tabs because for us it's not sufficient to only know where the order went and when it was made and what kind of and who the customer is. We also need to know what constituted that specific order. So information from this step and likewise, it's not enough for us to know just what constituted an order, because we also need to know who the customer was, where it went and when it was placed so inevitably were going to have to work with both these tabs, and we need to find a way to combine them or join them. So let's see how we can do that in table. I'm just gonna close this um, Excel file. For now, I don't need to save changes. And what we're going to do is we're going to help open up a tableau and we will connect to this daughter source. So we're going to connect to an Excel file, and here we've got the amazing mark. You open it up, and here right away we can see something different to what we normally used to on the left . There's actually three sub items that we can choose from. And these air the tabs that we just looked at, a list of orders, order breakdown and sales targets. So let's have a look at list of orders. If we drag it into here, as we normally do, we'll have a preview off the tab. That is list of orders, which fair enough. Now let's close that and drag order breakdown into this section. Now we have a preview of the order breakdown tab, same thing as we saw just now. So now what are we going to do? How we're going to connect them? Well, Tableau has a very convenient functionality that allows you to join these two files, and that's exactly what we're going to be do doing? We're going to be joining these two tabs. So let's first do it and then we'll discuss what we did. First, we're going to take list of orders and we'll drag it into this part off the daughter connection manager. And now we're going to take order breakdown, and we will also drag it in there. But we'll put it to the right of list of orders. And once you let go, you will see automatically. That table has come up with some sort of Aiken here, which is signaling to us that these two file tabs are now connected. And if we look at the, um, preview, there's many more combs now. So these columns here come from the first file to come from list of orders and then these columns on the right. Here they come from the second file. They come from the order breakdown, and if you click on this connection over here, you'll see what tablet did Tableau did an inner join. So now if you're not familiar with the term inner join, don't worry, because in the next section of the course we will talk in detail about inner joins left joins right joins full outer joints and so on, because it is quite an important topic in tableau and connecting to daughter. But for now, we'll just try to understand. What exactly did tableau do? Based on this description over here, you can kind of guess that tableau looked at order the order I d field in this, um, tab. And then it looks at the order I D field in this tab. And it matched the two off tabs based on this field. So basically, what that means is, um for whenever there was an order, I d off X Taboo. Looked for the same order idea in this file and attached it to the Rose in this file. So now that we know that the called the Order I D Field in the first tab is unique and it's not unique in the second, what that means is that for every order I d in the first tab there were they might have been several order ideas in the second time. Well, in that case, what happens is tableau will duplicate the rose from the first time. So let's have a look. An example of that. If you scroll down here to the very bottom. Uh, I noticed there was a few here. So you, as you can see here, these rows are duplicated, so you can see an old information in these columns is identical. So tableau did duplicate these rows and then connect them to associated Rose in the second tab. And here the rest of information is unique all, of course, because these are different items in that second full second tab. So what we did basically is we've created a new structure, a new table based on those two daughter sources and going forward from here, Tablet will be working with this table rather than with either of these. And that is a very, very powerful feature. That means that we've actually modified daughter. That tablet will be working for. Not that we've changed the daughter. We've modified the structure. It's no longer to separate tables. It's one table that has been joined and to, um acknowledges here. We'll just change the name from list of orders to, um, plus order breakdown. So if we click, um, just click. Anyway, here. Now the connection has been created and we go to shoot one. You'll see our connection here and now. Also, you can see that tableau has, um, Godal The columns as ah was featured in the daughter connection, but it's also separated them here to show you which file they are coming from, where he's coming from, the list of orders or from the order breakdown file. So that is how we join in tableau. And once again, don't worry if you're not entirely sure comfortable of what? Just what we just did, because there'll be a whole section on this stuff very soon in the course. So just follow along with what we did today. And, um, we'll get along with the tableaus part of the course. So the visualization part in this section and then we will recap again on joining in the joints, out of joints and so on. And even we'll talk about blending in the next section of the course. So I hope you enjoy this tutorial and Alec for seeing next time. Until then, happy analyzing 21. Creating a Map, Working with Hierarchies: Hello and welcome back to the course on tableau, and in today's tutorial, we will be creating a map and we will learn how to work of hierarchies. If you recall, the first time we created a map was in the very first section of the course. That time we create a map of the US, and we kind of analyzed how a certain store was performing across the different states of the US Today will be working with a map of Europe, and we will spend much more time on it so that we can understand exactly how to work with geographical daughter in tableau. So let's get straight to it. First thing we're going to do is we're going to save a workbook because we didn't do that last time, so we'll click save as section for there we go. And now we're going to start by creating our first hierarchy on Why do we need a hierarchy ? It well, that is because we have certain elements of geographical information in our data that we need to ah, tell tabla holiday work together and let's have a look at that. So here on the left, in the dimensions you can see right away that some fields have been picked up as geographical data, and the globe represents that some fields have been picked up as text, and some fields have bean picked up his state. And so here we have three elements off geographical daughter. That tableau recognizes its the city, the country on this state. Now region is also an element of geographical daughter. It's north, south, ah, central or west or East Europe. But in this case, Tableau doesn't have that geographical or that level of geographical information. Know that layer. So in this case, tableau doesn't recognize it, and thats okay for us because it's sufficient for us to work with these three. No. At the same time, these are all elements of geographical information. But we also know that a city can only be in one country. A country can only be in one state, so therefore there is a hierarchy and natural hearty. Then we have to, ah, show tableau, hard works and temblors already, um, prompting us to create a hierarchy here, and we can go ahead with that. But for now, we'll just delete this hurricane. That tableaux has prompted for us and we'll create all. So we'll just click remove hierarchy. And now we will start by creating old. The easiest way to do it is to take any off the elements, let's say City and drag it onto its apparent elements. So in this case country, and so now we will is tableaus, prompting us to create a hierarchy called Country City. But we'll just call it geography because we know that we will ADM or into this higher it you just know. So if we do that right away, you can see that country and city have been moved into this hierarchy separately, away from the rest of the dimensions. So now if we take state and we also move it in here, we can put them in between put in between. We can put it anywhere, but we know that state goes between country and city, so that's where we will put it. And now we have created national hierarchy for us to work with going forward. And so now what we can do is we can take country, and we can drag it into, um, our workspace. And once we've done that right away, you can see a map of Europe has appeared, so I'll just make this smaller so that we can zoom in a little bit. So a map of Europe has appeared, and the dots represent the countries that are in our data set. So there's United Kingdom, Germany, Norway and so on. No, you can also see this little plus sign. And the plus sign appears because there is a hierarchy that tableau knows about the one that we just created, and it knows that it can drill into the daughter further, and that's why it's allowing us to do it. So if we click the plus sign right away, you can see that instead of a dot for every country. Now we have a dot for every state. So let's zoom into Franz Foreign since and you can see here that in every single state of Franz there is a dot and as because we are looking at the level of granularity off state, Um, and that's because we have state as as you recall, um, whatever dimensions are listed on our A worksheet, that's the level of granularity that Teller's gonna be looking. So once again, we can click this plus sign on the state and that will drill in further into city. So now we have every dot represents the city. So we have a dot for every single city that our ah, that is president or daughter said So, um, there's a Genevieve Ilya. There is less really my pronunciation might not be the best, but, um, as you can see, there's lots more dots here right now, and in fact you can keep track of the number of marks on your chart or map, as we discussed in the bottom left corner here. Right now, there's 1000 and one marks, so that's quite a lot off data points, and we can really start working with this. In fact, we're going to go back one step, and we will leave the map at the level of granularity off a state so we'll just collapse that. And now let's go ahead and start working with this. So what we're going to do first things first is is always important to know how many if you have more than one year in your daughter and, um, you know, because you got to be careful not to aggregate information from different years. If you don't need that, so first thing we're going to do, they're going to take order date and drag it into filters. And we already know how to work with filters. Right? So, um, we're going to add it into filters here, and we will just choose, not range of dates. But we'll choose years. So next. And let's say we want to look at 2012 to start with, okay? And just as we did before, what we're going to do is we're going to create a quick filter show. Quick filter. Um, there it is our quick filter. So I'll just make the workbook a little bit smaller so we can fit up Rick filter in. And in this case, we obviously don't need all. So what we're going to do is customize show all value, we don't need it, and we will change this to a single value slider. So now you can slide along and you can see how the daughter changes. So that was the first thing that we wanted to do. And now working with a single year, what we're going to do is we're going to create some colors and some sizes on our charts. So first thing that we're going to do is we're going to say that we want to look at how many sales were done in every single of these every single one of these regions. So we're going to take sales and we'll drag it onto size and right away we can see that, um, there bubbles have changed size because and now they represent sales and they look a bit. Some also listen, increases size a little bit. Let's take it to this level, for instance, and then we'll go to colors and give it a border. Let's say a black border to make it kind of stand out a little bit. That's good. Now what we're going to do is we're going to create a calculated field, what we want to do and what was told, um, in the challenge. What we were told in the challenge is to look at the profit margin for every single state. So let's go ahead and do that. We need to create a field that will take the sum of profit and divided by the sum off sales , and that will give us the profit margin. So we're going to right click on profit. Here we will go to, um creates calculated field, and here we'll call it profit margin. We need some of profit. So it's important to take the sum of all the profits for all the orders in that specific region first and then divided by the sum of total sales for that region rather than divide , taking profit divided my cells and then taking the some. So it's important here to first sum up all the profits, sum up all the sales and then divide one by the other. Click apply. Okay, so we have profit margin. Oh, and now if we take profit margin and drag it onto color, which you will see is that the field here is called a G profit margin, which means aggregate of profit margin. Basically, it's telling us that this is a radiant, aggregated field because profit margin is a calculated field, which takes which first takes a sum of profit and devised by the some of cells. So tableau is telling us that this is not just a, um, a single value field. It's an actually aggregated field on just kind of warning us about that. Next we're going to do is we're going to just the colors and we're going to take, um, let's say it's of Red Green. Let's go Red Blue will apply that. And now we will say that, Ah, we want a specific levels off profit margin. So anything, um, below 0.5 miners there. A 0.5 is already very bad. Anything over 0.5 is great. So if I click apply, we'll get a child like that. And yeah, so that's That's pretty much it. That's what we wanted from all map. And now if we, ah, scroll around, we can see how, um, the profit margins and the sales changed over the years. And once again, if you put your mouse over any specific region or inspect civic state, it will tell you the country that state the sales and the profit margin for that ah specific period of time that you're looking at. So let's go up here because we can zoom out a bit because we've got, um, Sweden here, still gone off which Finland and so on so we can see how they're changing as well. What else? You can do is you can Ah, hello. Highlight things here So that say, you can do a square highlighting like that if you like. Um, but we'll talk more about this a bit in a bit when we're working with our first dashboard. So that's just the different types of highlighting you have in tableau. So have a play around with that. See what else you can do. Maybe you want to not look at profit margin, but, um, some other parameter or some other metric off how the region's or how the States are performing, Maybe you want to drill down to city level. So here, right away you can see we have many, many Mawr circles, and this is sharing the same thing. So basically, the profit margin for every city maybe don't want to see that maybe you can go back to country and look at individual countries rather than stay states. So lots of things you can do with this map here, and so I'll leave it at that for now. In the next tutorial, we will create a scatter plot and then in the tutorial. After that, we will finally create our first dashboard, where we will start combining work shifts. So I hope you enjoy this tutorial. And I look forward to seeing you next time. And until then, happy analyzing. 22. Creating a Scatter Plot, Applying Filters to Multiple Worksheets: Hello and welcome back to the course on Tableau. And today we will be creating a scatter plot. And we will also learn how to apply filters to multiple worksheets and her a Finally, we're going to create more than one worksheet in our tablet workbook, so that's gonna be fun. This get straight at it to start off with. We've got this map here in front of us that we worked with, Ah, last time. And as you remember, we have this filter that we're applying to the maps. We are looking at one specific year rather than aggregating across multiple years. So let's just remember that. And let's go ahead and create a second worksheet in this workbook. So to create on the worksheet, you got a click this button away here at the bottom which says new worksheet. So let's go ahead and do that once you click that it creates in your worksheet. And it's a good time now to rename a worksheet. So ah, you just double click on the worksheet name and he will say a map off your And now if we double click on 2nd 1 will say customer scatter plot. Okay, So let's get ahead with our customers. Scatter plot. So, as you remember, the first thing that we did in the previous tutorial was to make sure we're looking at the right time period of our daughter because it is important to remember when ah or no when your daughter includes multiple years or different time periods that you want to look at individually and because that's a common mistake. Sometimes people created dashboard and they forget to add the filter. And there, instead of looking at every single year by itself, they're looking at the some for all of the years. And that might not be what they're ah, intending or ah to see when they're designing the dashboard. So once again, what we can do is we can drag order, date into filter select years and, you know, do the same thing that we did lost him. But we're not going to do that because what we want to do is we want to look at the same year across all of our worksheets, and this is where we so if we had many, many more worksheets, we wanted to look at the same year across all of them. And so this is where we're going to learn how to apply a worksheet across many different apply filter across main, different worksheet. So to start off with, um, what we're going to do is we're going to, um, add some data into this worksheet, and then we'll apply the filter and I'll explain in a minute why we're doing it in that order. So let's say we want to look at some of sales in columns on, and we want to look at the sum of profit in rows. And so here. What has happened is Table has aggregated the total sum of sales for all of the years. All of the customers, all the regions for everything and the sum of profit as well. And now is just showing one dot And as you remember, if we want to disaggregated, we can either go to analysis and we can uncheck aggregate measures. And then we'll be showing ah, a dot for every single one or, um, let's just leave aggregate measures on. We can just add some information into the detail, changes granularity off the view, and that way tableau will automatically aggregate at that level of granularity. So how about we add to customer name into detail and right away we have a dot for every single customer. Um, So what we're going to do now is we will work with that, um, work to create that filter across multiple worksheets. So let's go to map of Europe. And as you remember, this filter that we have here on year, what we're going to do now is we're going to right click it and will say apply to worksheets and will say all using this daughter source. So that means any worksheet using his daughter source will automatically have this filter applied to it. You can also select worksheets, but, um are kind of recommend doing all using this daughter. So unless you have a specific case when you need to select specific directions, So let's go ahead and use it on all Ah, the worksheets that are using this data source. Click that, and right away you can see that a daughter base Aiken has appeared on the left of the filter, meaning that is being applied at the level off the daughter sources. So basically anywhere sheet that's using this data source will automatically have this filter plant. And if we go to customers can applaud. You will see right away that this filter has being applied here already. And if we right click and we say, ah that we would like to see a quick filter, you will see the quick filter on the left on the right Here it hasn't been formatted, so that's easy to fix, customize show all value, will just switch that off and then we'll just change to, um, the single value slider, just like in the Prince case. So now if I change it, if I go from 16,012 you'll see that this has changed as well. Over here, it's changed 2012 half ago, 2011 and go back. You will see that the filter has changed here as well. So this is kind of a filtered as we apply to all worships which are using this daughter source. Now you will find that if I go to these worksheets, the new ones that currently are not using any data source because there's no dot on the, um in the workspace. The filter has been applied, and that's simply because tablet doesn't know if this time it was work. She is going to be using his daughter. So so not because eventually you might add another daughter source and I use that one. And then that case, the filter won't be applied. So as soon as you drag anything from this, um, works from this daughter source onto the worksheet, let's say number of records and just drag it here. You will see right away that the filter has been applied, and that's how filters across different worksheets work. It's a very, very handy feature and actually took me some time to find out about it. And I used to just apply separate work separate filters to every worksheet and can be a nightmare when you have, like 20 or 30. Whereas when you have, um, when you use the work this filter that is applied across worksheets it's very easy to make sure you're All of your worksheets are showing the right information for that specific year or for that specific regional for whatever you're filtering on. Very good in terms of consistency. So let's go back, show customer, scatter plot and continue creating it. So what is this scatter plot currently showing us it is showing us the prophet bit profitability off customers. So basically, based on the sales that we made to the customer, what is the profit that were received in return from that customers? Well, so let's make this, um, scatter plot a little bit prettier because there's a lot of dots here and we can't really, um ah, country the say anything about, ah, the ones that are overlapping. Um, So what we're going to do is we're going to add some color, and the color that we're going to add is we're going to look at, ah profit margin because, in essence, if you take profit and divide by cells, that is your profit margin. And so if we take profit margin, which will recalculate field, which would create last time and we take a dragon onto color, you will see that the shapes have been colored. No. Now we're going to change the type of shape, so we'll just click shape. Um, even though we don't have anything on shape right now, um, we don't have a variable that controls this shape. What we can do is we can change the shape ourselves. So in this case, we want their circles. And like, last time, what we're going to do is we're going to change the color too red and blue. We'll click. Apply. Um, So next what we're going to do is, um, change the size of these bubbles. So if we go to size, make him a bit bigger, Well, that's obviously too big. So maybe somewhere there, Um, yeah, that looks OK. Maybe will also change the color in terms off levels. So we'll go to edit colors and will say, just like we did in the previous tutorial. Will say, minus 0.5. His hopes is already bad. So my 0.5 and 0.5 is already good, so apply. Okay, so that's already looking better. And now we've got map of Europe. We've got profitability of our customers and 01 more thing is because they do overlap here . What we can do is we can go to color and then change the transparency, so that set it at 75%. So now you can see the times when they overlap, and once again, this is already quite a good scatter plot that we've created so we can see how the customer profitability Ah, changes from customer to customer. And if we change the years, you can see how the profile changes overall. So here in 2013 you've got some very unprofitable customers. Ah, here you've got a bit of a different profile, more scattered. And also, if you need to do some investigations, you can just put your mouse over a Saturn dot here, and we'll tell you exactly who that customer is, what the prophet is, what the sales was with the profit margin for that customers for that given year. So that is a very handy tool to have right away. It can help you, like somebody who's analyzing this sales for the shop. They can just go and see. OK, the least profitable customers. Maybe, um, maybe something needs to be done there, some customer service service or, um, maybe those customers are pursing the wrong products or something. That and then you can look at the most profitable customers, and maybe they should be included in a loyalty program or something along those lines. So that's how we create scatter plots in tableau and in the next tutorial, we will finally create a very first dashboard and that will be super exciting. So I look forward to seeing you then until next time happy analyzing. 23. Let s Create our First Dashboard!: alone. Welcome back to your favorite course on Tableau, and today we're finally creating our very first dashboard Hooray! Congrats on getting this far is going to be super super fun, and you will see exactly how to create your first dashboard. It's going to be epic, so let's get straight to it here. We've got two tabs. We've got to work sheets that we re created. We've got the customers scatter plot and we've got the map off Europe. So now how do we put them both together onto one dashboard that when somebody's analyzing, he can see them together. So to create a dashboard, you need to click this second button over here, which says New dashboard. So let's go ahead and do that. And right away we've got a dashboard one created, and as you can see, it looks a bit different to a worksheet. Doesn't have dimensions and measures its rather got, um, the different worksheets that we have in our, um, tabla workbook, and he's got some layout specifications as you can choose. Like you can add images, you can add whipped pages, text, um, different horizontal vertical layouts. Um, it's got you could make objects floating or child, Um has got some other width and height parameters. It's more of a visual kind of representation were no longer doing, um, data mining or don investigation and analysis. We are creating a very pretty and powerful tool for somebody to do Don investigation, using the dashboards, that or the worksheets that we've created. So let's go ahead and do that. No, The first thing that we are going to do is we're going to drag our work sheets onto the dashboard. So let's take the map of Europe, and all you do is just just drag it on here and right away you can see it's filling up most of the space, and basically this dashboard is pretty much identical to a map of Europe. Um, we can roll a scroll over different ah states and will show is different information Now what we're going to do is we're going to add this scatter plot to this dashboard as well, and we're going to drag it. And as you can see, tableau is giving you some suggestions where you want to put it. So what we're going to do is we're going to put it here underneath our map. And there we go. So tableau has put this dashboard under Oma. Um, now, we obviously don't like thes scroll around buttons here because they shouldn't be. There s So what we're gonna do is we're going to go to the map and we'll make it a little bit smaller. So if you make him up just a bit smaller and you go back to dashboard, you will see that slowly you're kind of getting rid off those things. So we still got this vertical one. So let's make this smaller and maybe this a bit wider and maybe one more time. So we've still got both that unlike that. Then you can just drag it in the dashboard to fix it up to finally, and there we go. So we've got the map of Europe, and the customers can applaud both in this dashboard. So obviously this. Now we gotta decide on what we want to leave what we don't want to do. Um, the sales kind of size off the bubble, it doesn't really help us, because visually, it's very hard to compare this legend to would actually see, So let's get rid of it. It's no point in having it on the profit margin. Well, kind of. It's more. The red and blue is more to show us kind of positive and negatives we don't really care about, um how the different. Ah, like how they compare that This blue is exactly a 0.19 and this blue is 0.95 We won't be able to see that before I and same thing here. It's more over an aesthetically thing in this case because we already know that anything below the horizontal line is actually bad. So in this case, that aesthetic all thing in this case is just so that our eyes are our attention is drawn towards the red or the blue so we can quickly separate the good versus the bad and versus, like, the neutral, which are these gray ones. So in reality, we don't really need this, um, color religion. So let's get rid of it, too. Of course, we do need a year of order date, and now what I wanted to show you is, um, how to add this filter in case, um, it's not there. So let's let's assume that the filter wasn't there originally. So, um yeah, that's OK. What happened? There was I removed a I removed one of these, um, containers. So just put it back. So yeah, that's that's pretty. Another thing. That's good. Teoh. Good to know you can add these containers so horizontal vertical, and that will help you split up your dashboard into segments. So in this case, added a vertical containers so that now I can put things into the container. So here, we've got to dashboards. But we don't have that filter. How do we add that filtering? Ah, Well, what we can do is we look at this drop down for this, um, for the map. And here it says quick filters. And you can add the quick feel too ahead on year off order date on the same thing. You could have done it through this way. You can go here. Um, quick filters, and you can just choose the quick felt that you want to add. Eso just gonna actually close this because it's already created container for me. And with this quick filter, once again, you need to format it. So just go. Um What did we have single value slider and obviously we don't need also customize show all value Take it off and then you go so that you have your quick filter. And as you can see, as as you remember, because we said for this filter to be applied to all worksheets. So here you go apply to worksheets all using this daughter source. So it's basically the same as what we said on the map of Europe on, and it's applying it to all the work she's using this daughter source. So now when you click around, you will see that both of these charts or both of these worksheets are being affected by the filter, which is good, which is consistent. Which means that we know that in both cases were looking at the same year rather than not knowing what here we're looking at in which of these two worships Um, so that's how you create your first dashboard. That's the concept behind it. So dragon drop kind of style of operating. Um, in the next tutorial, we will learn how to do some really cool stuff. We will start ah, doing looking at action filter. So how to make Ah, each of these dashboards clickable so that the interact with each other some making a dash more interactive, and we'll look at some other cool stuff as well. In this section of the course, I look forward to seeing you next time, and until then, happy analyzing. 24. Adding an Interactive Action - Filter: hello and welcome back to the course on tableau. And in today's tutorial, we will learn how to make our dashboard interactive. So what do we mean by that? Well, what we want to do is we want to allow the user of this dashboard to drill into certain parts of the dashboard by just simply clicking on it. So, for instance, if the user wants to drill into certain state like, um, ill difference, for instance, um, he can just simply click on this bubble and then the customers can't applaud will automatically adjust to reflect on Lee the customers that live in that state. And same thing goes for any other state because that will add a lot of value to this dashboard into the users who going to be using it, because they'll be able to analyze difference geographical regions individually and separately. So let's see how we can do that. In order to do that, we need to add an action and in tableau, their two main types of actions. They're called filtering and highlighting. So let's go to the dashboard. Drop down here, Admiral, Click action here. You can see that if you want to add action. Um, you can choose between filter highlight. There's also third action called your L, which will take your person link, but we won't be looking at that for now. Um, instead, off adding an action here right now, what we will do is we will add an automatic action, which is much easier, and that will help us slowly get into this topic of actions. So what we're going to do is at the top of map of Europe. Well, look, click this drop down and we will select the Manu, which is called Uses Filter. So assumes you click that it's all done. So now, as soon as I click on ill difference, you will see that the scatter plot has been adjusted. If I click on England, it's also being adjusted. I click on Netherlands right away. You can see it's adjusted. So as you can see, I am able to now very easily select different um, states and see what's going on in each one of these states. So that is a very handy um, wait Journalist are So what exactly happened? Let's have a look in more detail now. If we go to dashboard and we go to actions. You will see that there is an action here. 80 and it's generated action, meaning it was added automatically. Now let's click on this generated action and we'll click edit. So here you can see that there's a few fields. First of all, what is the source off the action Dashboard one is our dashboard that we're looking at. And in Dashboard one, it is map of Europe that is the source of the action. The action is run on Lee when you select a certain element. And once you've selected an element, um, the action is applied to the target sheets. The target sheets are the customer scatter plot and the map of Europe once again. So in this case, what is going to do is it's going to filter the customer scatter plot. Um, it won't actually take out the rest of the values from the map of Europe because tableau is smart. It knows that if you take out the rest of the values from the map of Europe, then you won't be able to cook on something else. So, um, this have a look at that again, I click OK and now, once I'm selecting. As you can see, this is the source of the action. And these two are the targets of action. So in this case, the customers can applaud being the new work. Shit is being filtered. So was I click through the states. These customers are owned, the only the customers that live in that state are being left. So now what we're going to do is we're going to go to dashboards. We go back to actions that will adjust the sections to have a play around with it now, instead off a select Let's choose Hauver. What that will do is the action will be applied as soon as we hover over a, um dot on our map. So let's see how that works. Click OK, click. OK, and now let's hover over, Um, some of the states, as you can see our dashboard, I'm not clicking anything and the dashboard is being adjusted right away as we're just hovering over. And that is another way that you can present your dashboards. It might be more convenient in certain cases for you to be just two required to just over over these bubbles to get the second worksheet to adjust itself. Now let's look at the los option that we had there. If we go to dashboard actions and we click, edit or we select menu, what will happen is instead of adjusting the dashboard right away, were presented from anywhere we can toggle, um, the dashboard ourselves manually. But personally, I don't, um, use that often. So now let's do some more other things. So if we go to dashboard actions, edit Ah, let's leave it at select and let's explore this part of the dashboard. So what happens when we clear the selection? Well, we can either shoal values, which is happening now. So once we click somewhere else on the map, Alvar al Usar returned. Ah, what we can do is leave the filter, so let's have a look at that. So click OK, and now if I select a state in the neck like somewhere else, as you can see, all the states are shown again, but the filters stays on. So if I click somewhere else and I click back once again, the filter does not is not removed, which is probably not a good thing in this case because it is misleading. It looks like all the states are selected, but in reality not all the customers have shown. So let's change that. Go to edit. And you can also do exclude values. So have a look at that in your own time. It basically just will exclude all the values from your scatter plot. So we'll just click it, leave it back on, show old values like okay. And as soon as we select something and un selected, we once again have all values. So two more things that I wanted to show you the 1st 1 is how you create can create that specific filter on your own. So let's go to dashboard actions and will delete this filter. Remove it. Okay, so once again, now you can see that once I click, nothing happens. The scatter plot is not adjusted. If I go to dashboard, I want to add the filter on my own. I go to actions. I want to add action filter. Here. The source of our filter is a map of Europe. We can call a filter. Um, select geography because we don't call it selects Ted because we might want to change our dashboard and show it at the city level one day it will be a select type of filter show values upon clearing the filter and those through the target sheets. Okay, click. OK. And there you go. Now it's all working. And we created that filter all on our own. So that's that's great. That's ah, how you create actions manually. And the next thing I want to show you is that you can actually select multiple regions. So, um, I can select two or three. I'm just holding control on my keyboard, and I can select many Or I can use, um, the multiple select feature here in Tableau. So say, a rectangle, a selection. And here I've got the customers shown for all of those, um, states or I can do ah, circular selection. Say I want to select. So here I can select these customers or, ah, great one, which I like is, um, this freeform selection. So let's say I want to select all the people that are in France in the French States, and there you go. I've just selected everybody in France as easy as that. Another can analyze the customers that live in front. So that is how you create action filters in Tableau des Sports. And that is also how you can select many points on your map. And in the next tutorial, we will talk about the action, which is highlighting, and we will look at why highlighting hasn't been different. Two filters and what the intricacies are there. Have a play around with that, and I look forward to seeing you next time. Until then, happy analyzing. 25. Adding an Interactive Action - Highlighting: hello and welcome back to the course on tableau. In the previous tutorial, we looked at action filters in dashboards, and today we will look at how we can apply highlighting to dashboards. And also we'll discuss why highlighting is actually different to filtering. So let's get straight to it. Here. We've got the dashboard that were using last time, and still we've got the filter on action filters still applied. So ah, when we click on different states, as you can see, the scatter plot is adjusting automatically to to just show their customers that reside in that specific state. So now what we will do is we will go to dashboard actions and we will remove this action that we created. So we just click, remove, okay. And now if we select the different states, nothing happens to this catapult. Now, the gold, um, today is we want Instead of filtering this scatter plot, we actually want to see um, the customers highlighted. So we want all of the dots to remain, but only the relevant dots to stand out so that we know how they compare to the rest of the customers on the scatter plot and So the first thing that you might want to do is you go to dashboard actions and you go to add action and you click highlight. And here naturally use like map of Europe, select on the target sheets, our customers kind of blood mop of Europe and pretty much the same thing as we did with filtering. You click. OK, you click, OK, and then you click on a state and nothing happens. The group another state, nothing happened and so on. So how come did filtering work? But highlighting doesn't work. What is the difference? And this is an important point which a lot of people, um kind of don't will disregard. Basically, they don't, um, see the difference and therefore sometimes can fall into this trap assuming that highlighting works justice filtering. But it doesn't filter. The work shaded actually just highlights the values. In reality, it's not a simple is that there? There's one main difference between the two, and that is that filtering actually filters your daughter set and therefore allows you to reconstruct the scalpel. So when I have filtering on and I select this state, what happens in the background is tableau select all the rose off the daughter that are relevant to this state and Franz, which is ill difference, and it only leaves them. And then it removes all the rest of the rose in. Our daughter said that have nothing to do, feel difference. And so then the scatter plot is only working with the hell difference rose, and it is able to create a scatter plot based on the information. Now what happens with highlighting is that the doctor said, is actually not filtered, so that process is not running in the background. You're not deleting any or temporary deleting any rose from the doctor said. What you're asking dashboard to do is plug everything and at the same time highlight the customers that are relevant or related to ill difference. And that is where the problem occurs. And why is that? Well, that is because some of our customers and our data said, are actually from many different regions. So they are customers that are ordering products, um, both in Franz and in in the UK and so on. So one customer in this particular daughter said, is not attached to one particular state or even country. If you look through the daughter sexual find cases when, um, customers are in different states, countries and even cities, states and even countries. So let's have a look at that quickly. So here's our daughter said, Let's quickly add a filter So daughter filter and order the daughter by the customer name. So here you can see that right away I run, for instance, has ordered from Italy from the UK from Germany, from Netherlands, from Franz. And then, um let's say Adam here has ordered from Italy, UK, Franz and so on. So there are multiple customers that have ordered from multiple different regions, and that is what is confusing our highlighting. So when we ask, um, the dashboard to highlight everybody who has ordered from Franz, it cannot just highlight. For instance, if we go look at Erin, should should tableau highlight Aaron or should tableau not highlight Aaron? He has ordered from Franz. But in that case, if Tableau does highlight Aaron in this ah, in the scatter plot, what will happen is that we will see his, um, total profits. So here you can see that we've got profits listed sales in the profit margin. This is maxillary, but for Aaron it will be the same thing. What will happen is we will see the profit, the sales in the profit margin for his all of his orders that he did from all of the regions. And that is because once again, our daughter is not going to be filtered. So the Rose not relevant to ill difference, I'm not going to be removed from the daughter. They're still going to be in the scatter plot, and that is confusing tableau. So how can we highlight Aaron? Ah, with his two French orders? Or maybe Yeah, there was two. So this is Aaron, and he's made to orders from Franz. But at the same time, he's had ah lot of orders from other places. So if we highlight him, then we will be giving the user the wrong information. We will be telling him that Arens made this many orders altogether, but in reality, only two of them are from front. So that and that's why Tablet chooses not to highlight Aaron at all in order not to mislead the user. So what we can do in this case is we can actually change the granularity of us can report in order to include the state, and that way tableau will be able to easily operate at that level. So let's go to the customers. Can a plant. You can simply go to the worksheet here, or you can click this Ah, button over here, which is Goto worksheet, where you can click this button away here, which also says, Goto work shit. So once we're at the worksheet for the customer scatter plot, what we're going to do is we're going to change the granularity off the daughter right now . If you look at the bottom, there's 617 marks. Now. What we're going to add is the state, so we'll just drag state into detail and right away Ah, you can see there's more marks. In fact, if we go down here now, there is 1000 and 67 marks, and that is because customers can be, um, duplicated here if they are present in multiple states. So now when we go back to the dashboard, ah, we can see that once again, there's more daughter here, but also when we click, you can see that tableau is easily highlighting the right um daughter points here because it knows that it needs to highlight all of the customers that purchased from this region or that ah made their orders from this region. And if they are customers that, um ah had orders from multiple regions, it will only take those daughter points that irrelevant for those customers for these regions. And so now tableau is doing a great job in highlighting. If we go to dashboard on Goto, actions highlight, and we click Edit. Um, you will see here that you can actually select the target highlighting, and you can select the different field. So in this case, we want what what is happening is tableaus highlighting by state. So if we click OK, that will basically be the same result as what we saw just now. Um, probably one more thing is that you can, um, adjust this highlighting. So, um, you can specify the rules here so you can say Don't hell I buy stayed by highlight by country. And that way, wherever you click in the country, it will be highlighting the same customers that once again is misleading because you kind of the users thinking that it's highlighting the trouble is highlighting the specific state . Um, although the states are all highlighted on this part of the map, Um, but I would probably stay away from that. Just you do have that level of control. In my case, I'm just going to keep all fields. So there you go. That's ah, how highlighting works. And that's how it is different to actions. I mean, two filters in tableau action filters in tableau. So be careful of that. Action filters just to recap. Action filters work at the daughter level, they filter out the daughter, and then that daughter is supplied to the rest of the worksheets in your, um, attention your talent blow dashboard, whereas filters Oh, highlighting they don't hell. Leading does not ah take rose out of the daughter. And therefore it is still working the whole down ascent. And so, Ah, you have to be careful with the level of granularity off your different worksheets in your dashboard. So there you go. That is how highlighting works in tableau. I look forward to seeing you next time, and until then, happy analyzing 26. Section 5: Intro: Hello there. And I really missed you. I can't believe it, but I actually was thinking about this. And just for a while there, I missed you at this is funny. But anyway, if you are going through this course and you've gone this far Congrats. And I really hope you enjoyed creating the dashboard, your first dashboard in the previous section. It was fun. We did create scatter plots and maps, and so it was really cool. If you're just jumping in into this course in this section because you want to learn about daughter joining and blending than welcome on, we're going to thoroughly cover all of these topics because they are important. So what are we talking about in this section? Well, in tableau, obviously you're not always gonna work with just one piece of daughters, just one spreadsheet or one tab in the spreadsheet. Very often, you will have daughter coming from different sources at you. And, you know, that's just life with a daughter. Scientists, you have to get this daughter from wherever you can. And in the previous section, we even saw how to work with two tabs in one spreadsheet. Well, it gets even more complicated than that. Sometimes you might have thought to come from SQL some dollar from coming from Excel. Some daughter come from another system, some daughter coming from your Teradata, all these different daughter sources. CSC files anything, and you have to be able to cope with them and understand how to connect them and work with them all together. And so in Temple, there's two ways you can go about it. One way is joining data, and the other way is blending daughter. So a lot of the time and you'll hear me repeat this in this section that a lot of the time people underestimate the power of the to the differences between the two, and it's sometimes it takes people talk quite a while to get the head around everything. So what we want to do in this section is we want to make sure these topics are covered off once and for all, and you know exactly the difference between a joint and the blend and you know when to use . The joint went to blend how they work because there's a lot of intricate details around blends, for example, in tableau and also specific circumstances when you can and conscious a joint, so we'll be definitely covering off those topics. And by the end of this section, you'll know a love that and moreover, at the start, I do understand that everybody people might be coming from different backgrounds, and you might not have experienced full work of joins in the past. So if you've worked with SQL, then you do know what a join is. And I feel free to skip the first 123 tutorials off this section where we just talk about joins and what they are. But if you're not entirely comfortable with joins, I thought that it's important for us to cover that all first. So in the 1st 3 tutorials off this section, I will be explaining what what types of joins are. So, you know, joins our joints left, joins right joins, and so on will be looking at other topics surrounding joints. So when they're duplicate values and your join on when you need to join multiple fields, so those are three quick tutorials to just to get everybody to the same level, and then we'll be talking about the differences between joins and Bland's and I'll show you exactly how blends work and what they do, how they send Rick queries back to the daughter and then aggregate and then only join it together. And what kind of joining blend is that actually is, and at the end will throw in two bonus things, so we'll create a jewel access chart. So there was a really cool charts, and it's important to know how to create that when you have, like instead of having to charged on each other, you put one behind the other or the other way wrong. And that way you can present data in a more compact and more visual way for comparisons. And I'll show you some secrets around that. On the last tutorial, this section will be around using creating calculated fields across a blend. So that's a very specific topic, and it's a more advanced topics, so don't be afraid or scared when you get to it. It might sound a bit confusing at first, but I think it is important because even if you don't need it now, you can always come back to this course later on, when you do in cholera. That problem off creating calculate fields across different daughter sources inside a blend You trust me, you will one day get to that stage with you will need that information. So I just included in this section to make sure you're covered off. And there's no nasty surprises when you do require it. Eating it in your work. OK, so I look forward to seeing you throughout this section and until I see you next time happy analyzing. 27. Understanding how Left, Right, Inner, And Outer Joins Work: Hello and welcome back on today. We're talking about types of joints now joins our operations that are performed on tables in relational databases, so you would perform them in, um, SQL, Microsoft, SQL and Oracle and my SQL in many different platforms where the daughter is stored in a structured format. So let's have a look at some joints and understand how exactly they work to start off with . Let's assume that we have two tables, Table A and Table B, and in our example table A will have the falling rose. It's got three columns, customer, gender and age, and it's basically a table that is describing our customers. So we've got five customers. Adam, Benjamin, Jack, Nick and Susan. We've got their genders listed and there, um, ages. Now, if we go to Table B, it's a table off employees of a certain store of our store, basically, So it's got the employee named the title and the wage, and so what we're going to try and do is we're going to try and find out which of our customers are also our employees. So, basically, where where do we have matching rose in these two tables? And how are we going to do that? Will. Basically, if we look at the tables, we can see right away that Jack and Susan both up here in the customer and in the employee tables. So how do we do this from an SQL perspective for basically from a joining perspective? Um, well, if we start off with an inner join, then, uh, let's have a look at how it will work, and Inter join will take the two tables, and it will look at only their Intersect. So basically, if we're joining our tables on customer equals employee then and it's an inner join, then the remaining roles will only be the matching rose. So in this case, Jack is matched with Jack, and Susan is matched with Susan because we're just looking at the customer column in the left table and at the employee call him in the right table. So once that matching is done, the rest of the rose, which haven't matched are discarded, and the remaining table looks like this, so it only has those rows that match and kind of glues them together, and that's it. That's what the result often inner joint on these two tables would look like. Now let's have a look at a left joint, so there's a few different types of joints, but now we're going to proceed to the next. It was called a left outer join, and in short, it can also be called the Left Joint. So a left Join basically says that the primary table is the one on the left. Once again we're joining on, Um, the first column of the first able customer equals to the first calm of the second table, which is in play. And since the left table is the primary one, Rose cannot be discarded from the left table. Rose will only be discarded from the non primary table. So here Jack is measured. Jack Susan's match of Susan again, and then the rest of the rose in the second table are discarded because they didn't have a match. And so the resulting table will look like this. Where there was a match, the Rosa glued together and where there was no match of the Associated Combs are left blank . Um, Orson in SQL. Basically, those columns will be no old, so let's just keep them blank for no, that's how left joint works on. Basically, the main idea here is that the table and left off the joint is considered to be the primary table, and therefore rose cannot be discarded from the table. Now let's have a look at a right join a ride. Join works in a very similar way, but on this, in this case, the table on the right is the primary table. So once again, Jack is matched to Jack Susan. As much to Susan and the rest of the Rose in the left table are discarded because it is the secondary table. It's not the primary rose in the primary table. Another hand cannot be discarded, so the final result here is a table which looks like this once again. The two ah sets of columns have been glued together. And where there was no match on the left, um, the values in the columns are left blank or nolt. And finally, let's have a look at a full outer joint. So in a full outer joint, we're looking at the union off the two tables. Baylor. Probably unions, not the right word. We're looking at all of the roles in the two tables. And that's why, um, you see this? Those two circles in the Venn diagram up the top? Ah, fully yellow. And that means that we cannot discard or the joint will not discard any of the rules in any of the two tables. Ah, once again, we're looking for matches. So Jack is matched with Jack. Susan is master of Susan, and then what happens is no. Rosa discarded and the tables are glued together, and that is what the final result looks like. So on the right, there's blank spaces where there was no match to the, um, table on the left and on the left. There's black spaces where there was no match to the table on the right. So once again, I'll just go back to the previous slide, and here you will see the two table separately and now off to the joint. This is what the final table will look like. So that's how full outer joint works. And now legis quickly recap on the types of joins that we discussed. So we had a look at four different joints. The inner join, which only looks at the matching rose. Ah, the left joint, which keeps the left the table on the left as the primary temple, the right joined, which keeps the table on the right as the primary table on the full joint, or the full outer joint, which does not discard in euros from any of the tables. So in your work, you're probably going to be using inner joins and left joins mostly, And that is because right joints are rarely used. Ah, simply because a ride joint is the same as a left. Join just the tables. You just have to switch the tables around. So put the one on the right on the left and the one that was on the left on the right, and you'll get a left. Join once again. So most of the time, all personnel use inner joins on left joints. Um, sometimes you'll rarely find that people do require full joints for the task at hand. So those were the type of joints, and that brings us to the conclusion of today's tutorial and Lilac road. Seeing you next time 28. Joins With Duplicate Values: hello and welcome back. And in today's tutorial, we will be looking at duplicates and joints. And by that I mean what happens when the column that were joining on has duplicate values in one of the tables. In today's example, we'll be looking at two tables Table A and Table B Table A lists, orders that were conducted, person shop. It specifies the region and their status. So whether they were unpaid or whether they were paid Table B list the same orders but an itemized description of those orders. So in list the order number, the item that was sold within that order and the sales that were generated through the sale of that item. And as you can see, orders in table be can be duplicated because some orders consist off several items. For example, Order Number one consists over a chair and a desk, and so we're going to be looking at an example off an inner joint between these two tables . So basically we want to take the order number from Table A and use that to join table a two table, be also in the order number, so basically we want to connect the status of the order. Weather was paid or unpaid to the item and the sales of the order, and currently this information is contained within two separate tables. We want to bring it together from this image. You can see that when we join the two tables on the order number, there will be two matches in the second table to order number one. There will be one match in the second table to order number two. There will be three matches to order number three in the second table and there's no matches for ordinary before. So because this is an inner join, this row will be discarded from the final result. And what will happen now is as you can see, there's less rows in the table and left than on the table on the right. So every time there's a multiple match the rose that have been matched multiple times will be replicated, so duplicate or triplicate ID and so on. So in this particular case, the final table will look like this. And as you can see here, some rose off the table on the left, have been duplicated to match the number of rows in the table on the right, and that's completely normal. So this is the way the final table will look in our output. So that's what happens when there are duplicate valleys in the comb that were joining on. I hope you enjoyed today's tutorial, and I look forward to seeing you next time. 29. Joining on Multiple Fields: Hello and welcome back. Today we'll be talking about joining on multiple fields. To start off with this tutorial, I will show you an example when it is necessary to join on multiple fields. And I will show you what happens when you accidentally forget about joining on multiple fields. And finally, we will look at how we can rectify the situation and actually, in fact, join on several fields to get the right result. So let's get straight into it. Here. We've got two tables, table and table B Table A lists the orders that were conducted in our two stores, which are north and south. As you can see, we had two orders in the North store order number one and order number two. And in the South store, we had only order number one. And also the lists the customers Mike, Jack and Susan, Table B lists the itemized description off those orders. So we've also got the store location. We've got the order number and we've got item within the order and the sale made on that item. So here you can see right away that order number one in the north and store. I had two items sold a laptop and a months Order number two had one item which was the monitor and order number one in the south, and store had only one item, which was a camera. So now we want to connect the two tables and basically what we're after is we want to see how the sales that were made for each of the customers, the total sales for each with customers. So visually you can see right away how that works. But let's see how we can do it through joint. So if we were to go ahead and do a left joint so basically we want to attach the table on the right to the table left and if we were to just do a normal left join using one field, we would try to join on order number. So here, if we want to match order number in the left table to the right table, it will look something. This order number one will be matched to order number one in the first, drove the right table in the second row and in the fourth row. And as we can see, that's already incorrect because, um, we're matching order number one from the north and store to Order number one from the South and Storm. You wire this third match, but let's let's see what happens. Um, further down. So now if now order number two from the Northern Store will be a mass Jordan number two. That's because there's only one order number two in both of the stables. And then order number one from the south and store will actually be matched to three rose in the second table, which are order number one ordered from the Northern Store than the second item from Order number one in Northern Store and finally the only item from Order number one in 1000 store . So in total, the results in table will look like this. We will have, ah, three rows for north or noble 11 Roath for North Order number two and three rows for South Order number one. And as you can see, this is a mistake. There's an error because this highly inflates our sales. It looks like we've sold to laptops. It looks like we're sold to mice and two cameras, whereas in fact that's not true. So joining on a single field here can lead to incorrect results. So let's see how we can fix it. What we need to do and this you can see, um, naturally from the stables is we have to include information about the store in our joint. So we know that the order numbers are unique for each store. And so therefore, if we include the store now join, then we will avoid this whole problem. So let's see how that works at the on the top left here and circled in red. You can see that we're joining on order number from Table A equals older number from table beat and store from Table A equals store from table be. Let's see how this works. In fact, here we've got the the North Order number one being matched to two rows in the second table . So North Order number one, which is the laptop and North order number one, which is the mosque. And that's correct. Next in order, Uh, number two from the Northern Store is matched to only one row in the second table, which is the monitor for the Northern Order number two, which is also correct. And finally the south. And, um, number one order is matched to only one road, the second table because there's only one road that contains both the word south and the number one for the order. And that is the camera for that Susan board. So now if we perform their join, then the final resulting table will look like this. And as you can see here, the one row in the table on the left was duplicated to match the quantity of items which was two items board by Mike. And so in total, you can see that this time we've got the correct result. Ah, we can also assess how much each customer has bought, and they are no mistakes because of an incorrect. So that was a good example of how to use and joins in multiple fields and more importantly , why you need to do that in certain cases to avoid errors. I hope you enjoyed today's tutorial, and I look forward to seeing you next time 30. Data Blending in Tableau: Hello and welcome back to the course on tableau and in today's tutorial, where talking about daughter blending it's very exciting and at the same time controversial topic in tableau. And that's because daughter blending is often very underestimated. It is a feature that is not often used, but at the same time it is very powerful and should be used more. And moreover, at the beginning, it might be a bit difficult to distinguish between joining daughter and blending data. But don't worry. Today we will clarify all of that, and we'll put everything back in its place so that you can comfortably use and take full advantage off thes powerful features both joining and blending daughter. So just not awful if we're going to need a, um, brother, if you go to Superdawg, assigns dot com slash tableau and then you scroll down to section number five, joining and blending Daughter. Just download the very first file, which is airline comparison. So we'll just say that there we go and knowledge is bring this file up airline comparison. And as you can see here, we've got two tabs. The first tab has revenue for airline number one and It's split by period of financial year 2015 and financial year 2016 and it's played by multiple regions, and the second tab has revenue for airline number two. It is also split by year and region. As you can see, airline number two operates in less regions. And another thing to note is that in the first tab, the years called period. And in the second tab, the year is called a year, so you'll see why that's important in a few minutes. So I'm just gonna close that and we're going to open up a new tableaux workbook. Okay, And now we're going to connect our Excel file airline comparison. There it is. Ah, we're going to connect to the first tab here. So that's done. Now we're going to create another connection, and it will be to the same excel file. But now we will connect to the second tab. You know, if you go to our sheet one you will see here to daughter connections and ah, they represent the two different tabs in our Excel workbook. So what we're going to do now is we'll start visualising airline number one. We want to see um, how the revenue is split by a region, for instance. So we'll ignore year for now. We'll just some of the revenue for ah, the two years. And as you can see here, it's broken down by region now. And we can see, um, how the revenue ah, changes from region to region. Now what we want to do is they want to add airline number two to this visualization. So if we go to the second daughter source right away here, you can see this orange line on left. And you can see this link Aiken, which tells us that tableau is prepared to blend the daughter for us now. And so this is where we get to the topic of blending What is a blend? Well, remember how previously in one of the tutorials before this we created a joint for our daughter. So here in the daughter source, we connected some different sources of daughter like, for instance, like that we put in another element of daughter here, and we create an inner join. And then so we prepared all of the daughter before we actually worked with it in our workbooks. Well, now we haven't done that. But at the same time, tableau allows us to do that on the fly. What, while we're working with our workbooks and that is called Donna, blending and blending is kind of like a smart joint. So let's have ah bit. Moreover, play around with it and see how it works. What we're going to do now is we're going to drag revenue for the second airline also into our columns on right away. Now you can see that we have two elements in our Brazil ization. We've got the first set off bars and the second set of bars, which represents the second airline. And also, it's important to note that here in our control panel, we've got, um, two main elements. So this Ah, these controls are for, um, this airline and these controls are for this airline and these bars, and also you can control all of them through this future here. So let me just show you an example. If I want to change the color, for instance, I can change the call for everything or if I want to change something for this other bar chart. So we're just one of them for instance, I want to make it ah, line chart of center Barton. I can do that and then I can go into the second bar chart. I can change something else as well. I can change the color here if I want and things like that, so we'll just cancel this changes because we don't really need them. But keep that in mind that you can control these separately if you need to. Onda. If you need to control them together, then you just need to click this all feature here. So what It happened here? Well, Tableau knows that it can. It needs to join the two datasets in order to visualize them. Because, as you can see here, we're using region from airline number one and revenue from airline number one. But revenue. This revenue comes from airline number two, and that's why it's mark with this Ah little daughter base with a orange, I can work on it. And so tableau needs to somehow, um, aggregate revenue from airline number two at the level of region off airline number one. So how does it do it? Will Tableau knows that it needs to blend daughter, meaning that it needs to, um, joined the two daughters sources And how does it do it? It goes through the region variable here, and that's shown using this link. So is basically telling us that tableau has performed a left join from between the data sets and lay number one, an airline number two on the field, which is called Region. So it's kind of a joint on the fly. Um, so that's that's great. And the way region was picked up is because the name is the same. So region here is the same as region here, and that's how tableau understood that it needs to join on the region field. But what we actually want to do is we want to visualize not only by region, but also by, ah period, so by years. So if we go back to airline number one, um, and we take ah period here and we drag it into our, um, Rose, you'll see here. Financial year 2015. Financial year 2016. Eso no. One more thing we're going to do is for this chart on the left. We will take some revenue, will hold control that'll dragon into labels, and we will just format that quickly so that it's not, um, it's not in, um, millions. So there's less numbers. Currency. I just want millions. There we go on. Then we will take this revenue and drag it onto the label for this chart. And now we will formatted here as well currency just in millions. And now for the whole dashboard. We will format it and tell it to be 10 and bold. Okay, so hopefully you can see that a bit better now. Now what's happened is after we drag, um, periods, I'll just perform that again. So I'll take period out and I'll drag period into rows. You can see after a direct period intros. Um, the ah first Airlines daughter was split into two periods. So here you can see Africa, 10 million and Africa eight million. Um, Asia, 20 ages 16. So it is working here, but at the same time, the second airline, it's not being affected by the period variable. It's basically what it did, is just duplicated the data for the full daughter said. Instead of splitting it into two separate periods, why did that happen? Well, because tableau does not know how to connect how to connect to this period variable to connect the second data set to the period bearable as because we haven't established that connection. So we can fix that very easily if we go to Datta edit relationships. Remember how we talked about joining or multiple fields? Well, here we've only joined on region. You can see that that was picked up automatically. What we're going to do now is we're going to join on multiple fields. And now, instead of going just joining on region, we're going to join on period and year here. So if we do that click OK, you can see right away. This has being adjusted. So, um, what that did is now Tableau is joining these two datasets on two fields. And this is exactly what we talked about in that example with joining when ah, you need to join multiple fields. If you don't join in multiple fields when it is required, then you will duplicate values and you will over inflate the observations. So in this case, what happened is ah, double joined on to fields and those a period a region and year now, the reason why tablet didn't pick it up originally was because year has a different name. So what we'll do now is I'll show you how else you could have fixed that problem. So if we go to edit relationships and we take period out so we'll just put it back to automatic click, OK? You see, we have that problem where ah, the values of some tear and the bells of some here instead of being split. Now, what we can do is we can just go to one of these daughter sort set. So here we've got period. So how about we go to the second data set and we will hear Change the name so we'll rename it instead of year will call her Also period and which, you will see is that ta blow automatically right away. Picks up that this should be a connection. So now Tableau knows that the names of the same. So therefore it is joining um daughter on those two ah field. Or one more thing you should know is that if you take period out of your visualization right away, Tabal no longer needs to join on that field. It does know that there's a connection here, but it won't be joining on that field. And that is because it's that field is no longer part of your visualization, so you can manually switch it on if you want or switch it off. But it doesn't really effective solution in this case because it isn't participating in this visual. And so what that does is that, um, tableaux actually creates this joint on the fly, and the way Temple does it is a bit different to the way we were doing it manually back here in daughter sources when we were creating our own joint. Um, the way tableau does these blends is it's actually, Instead of joining the daughter at row level, it will first send queries to each of the daughter sets. It will aggregate them. So here you've got airline one, an airline to it will aggregate them to the level that is required at the level of granularity of the visualization. And then it will only join them. So in our case, for instance, before joining the daughter, it goes into L. A. In the into the airline. One daughter set, and it looks at the daughter it aggregate sit to the right level. So in our case it's the region level, and then it goes to the airline to daughter said. It aggregates the daughter to the region level as well, and then it brings back the aggregated valleys and joins them. And that is what daughter blending does. So it is a very, very smart left joint, and you can also see that it is a left join. Because here, one table is the primary table, the blue one and the or in the airline to table is actually the secondary table, which is marked with an orange mark. And, um, that from there you can see that it's a left turn. Because here you can see all of the regions which are present in airline in the airline one daughter base. And here you can, um, and they're joined to the airline to daughter based on therefore, these two a blank because they're not present in airline to, um so and finally, um, joining Ah, blending blending is actually done on a per sheet basis. So if I create a new sheet here, you can see right away there is no more, um blue or primary and secondary secondary daughter source, which means you can create a brand new blend and let's have a look an example here. If we start creating the blend with Airline to you will see that it will become the primary daughter source. So if we drag region into, um, Rose and now we drag revenue into columns and also revenue into label and make this a bit smaller, what you will see is that when we go to Ireland one it has become now those secondary for this sheet, it is the secondary daughter source. And if we take revenue and drag it into columns here, which you will notice is that there is no longer, um six. Ah Rose. Actually, before we do that, we have to fix something up because, um, some revenue you see this revenue has bean copied for both of the sheets, and that's not correct. So that could be a mistake. We need to take out revenue from here and drag using control revenue, the correct revenue and so you can see that has got that database Aiken. So what you can see here now is the important thing is that there's not six rows but only four, and that is because there's only four regions present in the airline. One daughter set and it's the left joint or sorry in the airline to daughter said, Because airline to is our primary table and this is a left join. So there's only four regions present in the airline to, daughter said. And if you recall when we talked about joins, when you do a left, join every everything a dozen match gives discarded. So in this case, North and South America got discarded from the final resulting table, and that is because blending is a very smart, but it is a left joint. Um, so that's pretty much it. That is how blending works. In tableau I I realize that this has been a rather lengthy tutorial, but it is important to understand how blending works. And we went through everything. Um, that is included in a blend. So we talked about the primary, the secondary tables. We talked about how to add our own elements to the joints or, in this case, period and region. We talked about how the the blend actually works, that it first aggregates the daughter, and then it only joins the daughter in, um, your final result. And we also looked at why the blend is actually a left join. And how you should be cautious of that when you are creating your visit realizations. So that's all for today. I hope you enjoyed this tutorial. And I look forward to seeing you next time. Until then, happy analyzing. 31. The Showdown: Joining Data v.s. Blending Data in Tableau: Hello and welcome back to the course on tableau. And in today's tutorial, we will be talking about the differences between daughter joining and daughter blending to get that topic out of the way once and for all. And also we will look at when it is appropriate to do a daughter blend in tableau. So let's get straight to it for today. We will need our daughter set. We need to go to super dot assigns dot com slash tableau. If you scroll down here to section five, joining and blending data, you will need the second daughter set, which is amazing. Marty, you now I won't download it because I already have it. It's basically the same one that we worked with in section four. So let's open that up and have a look at it on there it is. So here you can see um, here you can see that this started said has three tabs, um, whoever he talked about it. But we'll just quickly recap. So the list of orders tells us, um gives us a list of orders that had been conducted for the store. The date when the order was placed, customer name this city country region. Whether it was a home office that the daughter was placed for, ah, or it was a consumer or corporate office, different types off customers, basically Ah, shipping day shipping more. And this state off the country order breakdown gives us a breakdown off each order by the product that was contained within that order. So basically, this, um, field order ideas not unique in this tab because sometimes orders have multiple items within them. So here you can see an example that this order had both boasting markers and Elden folders and in the discount on the order of the sales of profit, not not on the order, actually on the product discount on the product, the sales on the product, profit on the product quantity, um, category. So whether it was office supplies, furniture or technology and subcategory So what we will be interested in today is actually this field category, it will be important for us. Onda Also, we've got the sale start a tab which gives us targets for the three different departments which are, ah, furniture, office supplies and technology. And it gives us the targets for the different months. Um off the daughter set. So what? The dollar value targets were for each of these departments for a certain month. So that sound daughter said. And what we will be looking to do today is we will want to compare, um, how the departments are meeting or not meeting their targets. But the caveat here is that that is not the only thing that we want to visualize. So it is only part off a greater dashboard that we're creating. So remember that dashboard that we created previously with the map and over was showing us different items. Soldiers bring it up, actually, just to So we remember what we're talking about. So I'll open up tableau and remember this dashboard here in section four that we created ah , which had the different maps off the different regions and then how the customers were which customers were profitable, which were profitable, and so on. So we still want to be able to create all this information. But at the same time, we want to be able to analyze how the departments are performing. Um, how the different departments performing. So let's go ahead and do that. So I'm gonna close this workbook on, we'll start a new one. And that's just because I want every section to be independent, so you can just pick up from any section and start working on it. So we're going to create a new connection. We're going to create a connection to our excel file and ah, Excel file is amazing. Mark, you And here we've got all three tabs, so we will recreate the joint that we created previously. So basically, we obviously want order breakdown, because here is got the sales. Um, and those are the values of the sales, and we need to compare the, um, sales to the targets. But the order breakdown tab does not have information on, um, the date. It does have the category, which is good, but doesn't have the date of the order. So we need the list of orders file, so we'll take list of orders well connected to order breakdown that creates an inner join. And now we have the order date. Then we have, um, the sale that was generated on that item and we have the category under which the item falls, which is perfect. And we still have all this other information that we need for the rest of the dashboard, which we just looked at. Um, Now, the question is, how do we ad sales targets into here? And the thing is that we can just simply drag it in Andi, create another join here. Well, it does work, but we're actually doing a very incorrect thing by doing that. And I have created a few slides apart, few PowerPoint slides just to explain or what exactly was going on. So let's have a look here. We've got two tables, everyone to join. So the table A plus B that we've already created through a joint and the table C, which is our sales targets Table A plus B has information on order. I d has the date has some more information. Has the item within that order has the category within which the item falls and has the sales that was generate on the item? And also, of course, there's lots of lots of other columns in there. And as you can see here, there are there instances where the order ideas and duplicated because in my consist of many items, so that's ah um, how are table looks Ah, the table that we've created, Table A plus B. Now we've also got table, see which we want to connect or somehow we want to link these two so that we can compare the sales to the targets. But thing is that the table C has a very different level of granularity level of granularity. Here is not item. So here the level of granularity is actually at an item level for each individual order. Where is here? The table is much less granular is Ah, it's got month, has got category and has got the target. So what that means is that if we do want to connect these two tables, then what will happen is we will have to roll this table up. We'll have to, um, roll it up by date and category in order to match this level of granularity. So basically, we will lose information on order I d and we will lose information and item. We will lose all of the information. Ah, except for date and category. And then we'll be able to take the sum of sales for that specific month for that specific category and compare it to target and basically that was what it means. We're losing all the other information if we're going to roll this table up, And that would have been fine if that is what we were looking for. If that is the only thing that we wanted to compare the total sales for a certain month for a certain category to their target, that would have been fine. But we can't do that, Um, because we still need to create the rest of the dashboard. Remember that caveat that we need to be able to create the rest of dashboard, so we need the rest of this information. So that way, we can just, um, roll up this table and join it to this table. And moreover, I'm just gonna end this So moreover, in tableau, if we were to drag sales targets here, it doesn't actually roll the daughter up for us. What it does is just performs an inner join. And as you recall, when they're many ah, fields. So it's joining here. You can see it's joining on category equals categories, not even including month. And when when that happens, it is duplicating lots of roads. So basically this what just happened here is a whole another mess. And if we wanted to even perform that rolled up joint, we would have to work on this a little bit. But the good news is we don't have to do that because we can use a blend. And that's exactly what we're going to do. We're going to see how we can use dot a blending in order to connect thes thes two daughters sources. So now, right now, we have one daughter source, which is called list of Orders. Plus, so I'm just going to rename this ah list of orders plus order breakdown. That's good. And now we're going to create another daughter source Excel and on the same file. But this time only the sales targets. And now over goto a sheet. You'll see we have two daughters. Sources list of orders plus order, breakdown and sales targets. So remember we talked about blending in the previous tutorial. Well, now we know that blending is a very smart join that can happen on the fly, and we're going to take advantage of that. We're going to create um, the visualization that is required through blending rather than joining and we're going to do that in the next tutorial. And today we're going to finish up on this on the reason why we won't be doing a join but rather be we're going to be doing and blend. And just to recap, the reason is that in this particular case, we would have had to aggregate our, um this data set, we would have had to aggregate our daughter set and we would lose information. So basically, the level of granularity off the two daughter sets is different, and therefore we cannot perform a joint. And so that's one of the reason why you would ever want to do a bland rather than a joint. And there's also a second reason why you would want to do a joint, and that is actually a bit more straightforward. It's when you are not able to do a joint because the daughter sources of different. So if, for example, your other daughter sources not and is not the same excel file, but it is our other say, a C S V file or a tablet sir follower, my skin, a Microsoft SQL database or something that if the daughter sources are different than tableau won't let you do it. Join you will have to be blending the daughter. So just keep that in mind that there's two reasons why you would want to do a blend. One is, um, low. Different level of granularity of the daughter sets on number two is, um, the doctor says are just basically different types off data sources. So that's all for today. I hope you enjoy the tutorial, and next time we will create this blend will be quite an exciting and very visual tutorial . So I look forward to seeing and then and until next time, happy analyzing. 32. Dual Axis Chart: Hello and welcome back to the course on Tableau. In the previous tutorial, we did all the groundwork in connecting to our daughter sources. And today we get to do the fun part. We get to create the visualization. So what will we be talking about today? Well, first of all, off course will be talking about blending and more advanced blending. So you will see Ah, a really life example of how to apply, blending and get ah results. And also you will learn how to do a dual axis chart. So I will show you how to create a dual axis charge today, which is quite a valuable skill to have in terms of your tableau dash boarding and creating cool visuals. So let's get straight to it. Here. As you recall, we have two daughter sets, more data sources, list of orders plus order breakdown which will tell us the dates when CERN items were sold when orders were made, and how those orders are broken down into two different items. And what's the sales on those items were and also we have the sales targets, Donna said, which gives us the targets for our sales for the different departments for the separate months. So as you recall the level of granularity for these two donna sources, different sales targets are, um, at the level off detail off a category and list of orders plus order breakdown are actually at a much more granular level. They are at the level off items which constitute orders. So let's go ahead and start creating our visual. Just start off with. We're going to want to visualize by a month. So we're going to track the order date into columns, and we're going to convert this into a month. So we're already used to that. We know what's going on here. Next, we're going to look for sales. So we've got the sales here in the measures and we're going to put sales on Child Rose. And right now that gives us automatically a line chart. But we're going to change that to a bar chart because that is a bit more representative in our case, a better representation. So there we go. It might be a bit, um, in this particular instance about me a bit too cluttered, so we'll just make it the reduced the size to give some room between the bars. OK, so that's our sales for that for every single month, the total sales for all of the departments. So what else we can do now is we can take the category and drag the category into Let's say , um, we can drag it into color, which will give us these bars like the bars and our colored into three colors because of the different categories. But we want to visualize the category separately. So we're going to take categories again, and we're going to drag them into Rose. And this gives us categories separately. Here. Um, now, this is a bit too big to fit normalization so will reduce the size. And there you go. So there you have how the categories or the different departments. Furniture, office supplies and technology have been performing since the start of 2011 all the way up to 2015. So what we want to do now is we want to add in the sales targets for these departments and see how they have or have not been meeting those sales targets. So where is that dot allocated? Well, it's located in our second daughter source sale starts this. Look on that here. Right away. You can see. Ah, that's familiar. Orange line on the left. Meaning that this is a potential secondary daughter source to all visualization where you have a primary daughter sourcing is mark here with a blue ah, little check Mark and right away Tableau has already recognised. That category is a potential field that it conjoined. These two daughter sits on because once again, the name of the field is the same in both. Daughter says we have category here, and we have category here on the reason why this link is already orange. Not great is because, as you recall category is already part of our visualization. So if category weren't a no visualization, this link would be grace, So we can have a look at that if we just whoops. If we just take category out momentarily, you can see that the link is great because tableau recognizes that this field is not a part of the visualization. So they might not be a need to join in this field. So we're going to put category back by pressing controls that Okay, So how do we get our Ah, dates into this or sorry, no dates. How do we get our targets into this realization? Well, first things first, we know that our joint has to be performed not only on category, but also on month off order date. And that is because, um, as you recall, sometimes we have to join in many fields, and in this particular case, the sales targets are set at the month level, so they're set for categories or for the different departments. But there said at the month level. So let's go back to the daughter source and have a look here. You can see that for every single month for the category furniture. There's a separate cell started for every single month. So therefore, when we are joining two or blending to our existing daughter, we have to blend not just that rolled up category level, but also we have to include the month off order date granularity. If we just blend right now with only category as our, um, feel, that tableau will be blending on. What will happen is tableau will. As you remember, tableau sends separate queries to each daughter. Set it aggregate stew. The required level of granularity, and then it brings the daughter back and blends it. So in this case, what would happen is tableau would go back. It would take a lot of these rows for furniture. It would roll them up. So to take the some of the target it would disregard month and would bring back the some of the target for furniture. And it would blend it to every single row here. So that's not what we want. We can have a look at that. So if we take Target and we drag it into in here, you will see and let's just make it, um, so we've opened up the target control panel. We'll just take out the category from color and will just drag it into details so that it doesn't affect the color. Here. You can see that the target is always the same. 621,000 which is unrealistic, not the right target Here. It's also the same, and here is also the same Eso It's not changing month to month, and that is because we're not aggregating at us or month of order. Date is being aggregated. It's not being considered as ah level of granularity for our chart. So let's go ahead and fix that. As I recall, we can control the blend or the how the blend is being created through this control box here. So we're going to go to daughter edit relationships and here you can see we've got the automatic field that has been selected. So now we're going to change it to custom will keep category, but also will add in a new one here. We want to use order date, but we want to use month of order date and join on, um, also month of order date. That's good. But also, month is not just enough because as you remember these air categorical variables, we need to also take the one above month, which is year. So we have to make sure that the year is also included. Others will mix up different months from different years, so we'll take year of order date on this side, and here will also take year of order date. And if we click OK, now, As you can see, there's a link, and now the category or the targets have bean adjusted, and as you can see there reflecting what is the reality, and we can easily check that. So let's say January 2011 sales target for furniture was 5000 or $10,000. If we go to the daughter source sales target for furniture and generally 2011 was $10,000 it's gradually increasing. So that's great, Andi. Now, let's just quickly change this, um, from a bar chart to an area chart because it looks better like that. And let's quickly have a look at the different targets that these different departments have set themselves so you can see that the furniture department has a very linear growing target. So it's basically got a, um, coefficient that every month the sales should increase by certain amount. Then the office supplies department has quarterly targets, or every three months. The target is different. The monthly target is different, so they basically review their targets every quarter and adjust them according basically decision seasonality or expect expected supplies and things like that. And finally, the technology department reviews their targets annually and sets them says the same target for the whole year, so every month will have the same target. So it's very interesting how the different departments have different targets and different ways of setting them. And you can see this right away through the daughter, even though fault talking to management and understanding their takes on it right away. You already have this information that so That's a very cool part of daughter Discovery. Um, that is ah, the targets below the actuals. What we want to do now is we want to combine these charts so we can actually visually compare them very easily and seamlessly. So what we're going to do is we're going to create a dual axis chart, and it is actually much easier than it sounds. So it might. It might be very hard to do in Excel in Tableau is extremely simple. And I'm going to show you right now how to do it. So all you have to do is you just right Click on your target here and you click do Alexis. And then one more thing which a lot of people forget. Very important second step in a dual axis start right away. You're right. Click on this axis on the right here and you click Synchronize access. That is very, very important Because if you don't Ah, as you can see right now, they're aligned. So 40,000 of the toe, 40,000 stop here. But if you don't synchronize you like I press controls it here. So this is synchronized. This is not synchronised. You can see that they have separate accesses. And that way you can get really confused and the people reading the chart can get the wrong insights. So we're going to synchronize access. Make sure you do that every time, and that finalizes Ah, the post of creating a dual axis chart. Of course, you can make adjustments further down the track, but this is pretty much what it looks like. And from here, you can get insights into each one of the department, so you can see when they're above the, um above there, target their meeting the target or exceeding it when they're below their Not so here again , you can see the same thing. Um, right now, the grey area charters in front off the of our bar chart. We want to put it if you want to put it behind, we have to just take some target here and drag it to the left, and that will switch places. As you can see, it looks much better now. The great chart is behind, and you can visually compare for every department kind of see how they're performing along the way. So what I'm going to do is not going to make this bit bigger. So the child looks so we can see the chart a bit better with bigger bars and increase the size of the bars. So go to, um, sales size increase. So, as you can see, that already looks really good, starting to look very good. Um, that's how you create a dual axis chart and tableau. Remember about synchronizing the axes. It's very important, and that brings us to the conclusion for today. Next time we will take this chart one step further, and we'll introduce a calculated field within the blend, which is a whole different old separate topic and tableau. And it's important to know how to do that, and that will hopefully finalize this chart for us. So I hope you enjoyed today's tutorial. I look forward to see you next time, and until then, happy analyzing 33. Creating Calculated Fields in a Blend (Advanced Topic): hello and welcome back to the course on tableau. In the previous tutorial, we created this beautiful visualization in front of us, which allows us to compare the actual sales off the different departments restored to their target sales. And today we will finish up with blending, and what we will do is we will talk about how to create a calculated field within a blend. And what that means is, how do we create a calculated field that requires daughter elements from both of the tables , which are being blended Now? I feel that this is an important topic that I should share with you because you will be creating ah lot of calculated feels along the way when you work with tableau, and when it comes to creating calculate fields within a blend, it's a bit different. They are certain specifics that you need to be aware of. So I just wanted to make sure we cover off this topic so that you're not in for any surprises along the way when you are working with tableau in your roll. So let's get ah ahead. Let's go ahead and get straight to it. Here. We've got our, um charts, and what we will be looking to do is for each one of the departments. We will want to look at the difference between the actual sales and the target cell. So we want to create a chart which will be taking every single bar and subtracting the target and seeing whether, basically, the bar the remainder of the bar is above zero billows around. That will allow us to very quickly see how the departments of performing now, because adding another chart will increase the size of this work shit. We might want to consider, um, taking these departments and looking them looking at them separately so that it's not too cluttered because we already have. Basically, right now we have six charts on this worksheet. We've got the targets which are in Grey in the background, and we have the actual sales, which are these bars in the front. So if we add another charge for every single one of the departments that will take it to nine charts, that might be a bit overwhelming for the user. So we want to take care of the user, and that's why we're going to, um, kind of simplify this chart a little bit, and we can very easily do that by taking the category out of Rose and putting it into a filter. So that's we're going to do. We're going to take category and drag it from Rose to filter. And right away we've got this filter settings that come up. We're gonna each click, OK? And what that gives us is quite a crazy chart right away because we are looking at everything at the same time. What we will do is we will take this and we'll click show quick filter. Now I'm going to reduce the size of the chart a little bit so I can zoom in and so that you can see the filter at the same time. And we're going to reduce the size of the bar. So that's just for for us. Okay, so that's what our chart looks like. Of course, we don't want to see everything at the same time, we're trying to get away from that. So first of all, we're going to, um, customize or change this filter to a single value list, and then we'll take out the well ah, value. So we'll take go customize show all value taking off, and now we can simply click through our departments and we'll see the chart for each one of them, which is great. Now, at this point, which you might be seeing is something different and not a worry. I'll be able to help out right away. So, um, perhaps what you're seeing looks something like this for after you've taken category out off the Rose and you put into Filter. What's happened is now when you click over from ah, the different three different apartments, you see the total target for all, the department said of the individual target. And that can happen. That just means that what you did by taking category out off Rose is it's just a filter now , so it's no longer a level of granularity off the view and tableau no longer aggregate. It's the daughter at that level. It ignores that level of granularity when it's doing this blend, and why that happened is because perhaps in your some of target in this control window when you in the previous tutorial, when you removed category from color is to make the target gray, You didn't put it into detail, but you're rather just removed it completely. So right now what's happening is for this chart, this great chart in the background here. Um, if you look at the look at the worksheet right now, you will see that category is nowhere to be seen as a level of granularity. Ignore it as a filter because of filtered just filters daughter. But your target your categories knowledge in columns. It's not in rows. It's nowhere to be seen in this control panel. And what that means is right away Tableau no longer knows you're no longer regards. Categorias a level of detail and will not aggregate at that level. Will ignore. You can fix that once again by taking category back into the rose right away. As you can see now, the categories correct, um, and you can click through. But we didn't want to do that. We wanted to keep category just as a level of granularity, but without actually being in our chart. So we'll take category out of here, and we'll just drag category into the detail. Just make sure it's there. It might be there if you if you let put it there in the previous two term might be already there. And that way you're seeing everything correct. So just make sure that that's the case, because this kind of shows that w