Tableau Full Course 2026 | Tableau Tutorial For Beginners | Tableau Developer Course | Simplilearn

Every time a company checks sales performance, tracks customer behavior, compares monthly revenue, studies, market trends are present, data in a very simple dashboard. Data visualization is working behind the scenes and one of the most popular tools used for this is Tableau because it helps turn raw data into clear charts, dashboards, and business insights. Hey everyone, welcome to this Tableau training course by simply learn. In this course, we are starting by understanding what Tableau is, why is it used and how it help businesses make better decisions using data. So you will learn how to connect data sources, work with worksheets, create visualizations and understand the Tableau interface in a very simple way. We'll then move into important tablet concepts like dimensions, measures, charts, filters, dashboards, stories, joins, relationships, cardality, data blending, map, heat maps, tree maps, hierarchies. Now, these concepts will help you understand how to organize data and present it in a visual format. After that, we'll be exploring how to build dashboards, combine data from multiple sources, choose the right chart for the right business problem, and create visual reports that are easy to understand. And by the end of this course, you will have a strong practical understanding of how Tableau is used to analyze data, create dashboard and share meaningful insights. So let's get started. Also, if you are interested in building a strong career in data analytics, I highly recommend you checking out this data analyst certification course by Simply. This course gives you industry recognized master certificate from Simply along with individual certificates from Microsoft that you can showcase to potential employers. a real boost for your resume. You'll be mastering key tools like Excel, SQL, Python, Tableau, PowerBI. Work on real projects to build practical skills and learn how to turn raw data into insights that drive better business decisions. Plus, job assist helps you prepare for interviews and get noticed by top hiring companies. This course is designed to help you gain the skills and confidence needed to step into high demand data roles. So if you're serious about a data career, this program is definitely worth exploring. Now before we move on, here's a small quiz question for you. Which tabular feature is mainly used to combine multiple charts in one view? Worksheet, dashboard, filter, measure? Let me know your answers in the comment section below. Usually we see that Tableau is used for data visualization. Tableau is used for uh reporting purposes, right? That's what we are using it for. So before we go ahead and start with it, can you tell me how uh what is data visualization let's cons uh understand the term first and then we will move forward with Tableau. Now let me define visualization for you in a very technical manner. All right, let's understand it in a very technical manner. So let's say okay these are the employee ids. These are the employee ids and uh after uh okay. So these are the employee ids and this is the sales done by them. This is the sales done by them. Let me make it easier right now. Okay. So this is the sales done by them here. It's a small data set. Now we need to analyze this data set. So how do we analyze this data set? We have to create a report out of it. Right? So let's say I I want to create a report here. We where I have employee ids where I have employee ids and in front of it how much total sales they have done. Now help me to create this report everyone. Okay. Help me to create this report. Can you tell me what should I write under employee ids? Under employee ids column what should I write pay out we are going to understand what visualization is right without duplicates E1 E2 E3 should be written correct your unique ids only very good so this is E1 E2 E3 now what should be in in uh in front of even everyone. What should be in front of even? Let me write uh the even number here. Now tell me what's the total of E1 15. What is the total of E2? Nine. Nine. S. This has got nothing to do with central tendencies. It's a very simple report. Employee wise, total sales. Who has done better? It's a very simple report. Right. What is E3 everyone? Yes. Now this is a report. Now as per the definition here, this report should be presented in a pictorial format. That's what how all of you all of you have defined the uh the data visualization right pictorial representation of data. So we I cannot go ahead and pictorially represent this data. We have to first create a report and the reports are presented at as visualization. Correct? Now how do we represent this into a visual visual here? Let me take you back to the middle school. Do we remember x-axis and y axis? Yes. And uh here it starts with zero. Uh how many of you remember this? Yes. Great. So tell me what should I keep at X-axis? Uh employee ID or total sales? What I should keep at X-axis? Let's go with the uh majority here. Employee ids it means on Y-axis we go with total sales. We go with total sales. Yes. Since now we are going with the total sales and the employee ids everyone. It means we have to also go ahead and make the tick marks. Do you remember those tick marks that if this is zero then uh here it will be five. Somewhere here it will be 10 and then 15 then 20 like this. These are tick marks. Yes. With certain gaps. Right. Right. Absolutely right. And in the employee ids of course we have three employees. So we'll be tagging all the employees here that this is for E1, this is for E2, this is for E3. What we are doing here? This is visualization. This is this is visualization. What we're doing here right now. Now next what is even everyone? What's even 15? So how do we match that? that this is 15 right this is E1 this is E1 so wherever that point is intersecting that that's where we pointed right E1 and 15 now E2 and 9 so 9 will come somewhere here this is E2 so the second point will come here E3 is 15 again so this is E3 and uh this is coming back here and That's that's 15. Now we have went ahead and we have we have made the data points here. These data points are currently exactly showing up what is in the report. Yes or no? Do we understand this part? Everyone now it is up to us that how we want to go ahead and visualize this particular visualize this particular point. What does that mean? Meaning this data point now can have and these data points. Okay, positions are decided. Positions are decided. Correct? Now to these positions here, we can give any shape we want. We can decide size and color of shapes. Size and color of shape with whatever way we want. We can also go ahead and add images of those employees there or uh images of anything there or maybe icons we want to place there. So I can go ahead and create bar charts if I want. If you want, you can go ahead and uh create a line chart. If you join these together, you can create a line chart. Okay? If you want something else, you can go ahead and uh create an area chart. You fill up the color inside it and this becomes an area chart. So now you have an area chart here. So meaning here is what is data visualization? Data visualization is the representation of values and reports via several visual indicators. Several visual indicators. Several visual indicators. What visual indicators are? These are the visual indicators. Position of the data point. Then which shape do you decide? Which size do you decide? Which color do you decide? Maybe you want to go ahead and uh give uh just bars or just lines or even not that you just want to go ahead and give multiple different sizes of colors here. Okay, you want to give multiple sizes here or maybe different colors based on employees. Now this all depends on you. Maybe you want to give different colors based on So now this all depends on you. Okay, that's what data visualization is and that's what we are going to learn in Tableau. So in Tableau we are going to go ahead and learn that how do we go uh and get the data inside Tableau and uh then how do we create reports in Tableau multiple different types of calculations we do there and then how do we create multiple different types of visualization that will effectively communicate what we want to tell to the end audience. Okay. So I will give you the visualization here. Okay. Generally we call it this. You all know about that. Why do we do this? Because we want to identify trends and patterns which are not uh patterns and outliers which are generally we cannot simply see on a data like this and visualize. Now uh working on the definition I have given you look at this example right now. You'll understand my definition that I've given you here very clearly. Look at this data set. Look at this uh entire chart. Okay. In this chart here, you have got x-axis showing income. Meaning from left to right income increases. From bottom to top life expectancy of individual increases. Each of the circle represents individual countries. So the position of circle is telling us that how much income is there and what is their life expectancy. Lower income, lower expectancy, higher income, higher expectancy, average income, all right, average expectancy. So position is telling us about income versus life expectancy. Now the size is of the circle is telling us about population. Size of circle is telling us about population. and color of the circles are representing continents. So this chart is utilizing all the visual indicators that there are and at the background is showing ears. Uh it has a YouTube video. If you go to YouTube and find professor Hans Ross link, okay, there's a YouTube video. So at the background the all the circles that you see they move from I think 1800s till 2019. So they move the entire cohort will move and the background year will change too. So this is the very versatile and perfect example of visualization. Now uh tableau is not the only one that is available here for visualization. Okay. There are many others too. Have you heard of any other names other than mentioned here? PowerBI Looker, Mattplot Lip, Seaborn, Zoho, Clickview, Clicksense. Yes. Any other name you have heard about or you have worked within your company? Can you mention that name in the chat box which you have used to create charts? Excel. Yes, correct. PowerBI is here. Other than these wow barb plot lab correct pbd is not used for visualization bra that is ux pbd doesn't analyze data it doesn't create charts is there excel is already there. So yes you are uh say uh in market currently there are three major players all right Tableau BI and click view in they are almost similar okay but there are few quite differences between them for example PowerBI require DAX and more uh and advanced knowledge on Excel to use PowerBI effectively plus you should have uh some kind of programming knowledge too to write DAX because DAX is the only way it understands the calculation. Click sense or click view here it uh for a small uh it requires a lot of programming. So if anyone is from a programming background it is easier for them to adapt it is very very different otherwise. All right. So and now we have Tableau. So let's understand about why Tableau here. Now next here is storytelling with data. What is this about? Let's understand here anywhere whether you use tabloo, powerbi, excel, matt, plot lib, anything python or anything else to analyze your data. Why are we doing so? Why do we analyze data? What is the requirement of that? To solve business problems to understand data is moving in transaction. Why do I need to understand that? Let's uh get this straight. Okay. It is important to understand before we move forward in real time right in real time uh you will be given an objective uh problem to solve okay a problem to solve. So these are very generic answers right to take a decision to solve null values to figure out a pattern. These are very general ideas here. What what happens in real time? Let's understand that. Okay. Your objective is to solve a problem. What kind of problem here? Right? What kind of problem here? For example, they might tell ask you that see I want to increase sales by 10% of insurance product of insurance product by next quarter. You tell me the strategy. Figure out the strategy. Okay. Or you have been asked here to reduce defects to reduce number of number of defects in finished products because they figured out that in the laptop that they are producing right every laptop has minimum uh 10 on an average 10 defects are there. So we have to send them back get them corrected and then get it out the product line. So how do we reduce the number of defects? Or they might ask you to find the smallest way to find the smallest or efficient way efficient way to move your goods across warehouses across warehouses or they want to launch a new product. Okay. And you need to figure out when and where to launch it. So in real time these are the kind of objectives that you will be given in. It is not like find a pattern, find out whom to sell, how to sell or they or you're given a very simple question here that go ahead and find customers find customers to whom to whom uh we should offer we should offer uh discounts and coupons discounts and coupons. So who is that person? Who is that group of persons? So these are the problems are actually solved on the grounds. Okay. Now all of this here all of this here are the objective. These are the problems to solve. So what do you do here? First thing that you do here is you start collecting the data that what from where how much data we need from where do I need the data set. Okay. I need employee data who is working on that product line. I need uh past 6 months data from multiple uh plants how they are doing. I want exact defects what are listed out so that I know which defects are there. Then uh how are those defects are caused? Uh on which machine on which exact step these defects are caused in that particular uh part of the laptop and who is working on that? Who is uh controlling that robot? Okay, who is that employee working on that particular shift? are they causing it or the product wear and tear no maintenance has happened. So you have to figure out what is going on currently and why it is going on, how I can make better, what is the solution for this. You create a strategy mathematically and with the domain knowledge of course and the calculations happen within your industry. You are in finance, you're in BFSI, you are in insurance, you know your calculations needed to be done and the cost needed to be calculated. Okay? So you know how that is has to be taken care of. You figure out a solution based on your domain knowledge and experience and uh how much it will cost to apply that apply that solution and how much cost recovery you are going to do there and then you go ahead and you tell them that this is how the future looks. If I you go ahead and apply my solution and this is the solution I am proposing which one of the solutions do you think we should apply now the end users there all the all the business process managers your directors CEOs and multiple different managers those who are responsible for finalizing the decision then they go ahead they finalize one of these solutions and they ask you to run a test a test run of your solution and then you test run the solution you again collect the data, you again analyze it, what happened, why it happened. If you're able to prove that this happened because of your solution, then you go ahead, you present it to them again and then it is launched on the fuller scale. So this is how it happens. It is every time a cyclical process, every time a cyclical process. So this is how in uh on the grounds this is how it works. uh yes if it is already in the market of course we will reduce the defect okay because uh wear and tear happens and sometimes something is going wrong in the product line maybe employees are not properly trained maybe uh robot has wear and tear it has not been taken taken care by maybe there have been there has been layoffs and something has not been taken care of so there can be many reasons to it we have to find one prove one and get a solution for that this is how it works in real time. Are we clear everyone? About what happens in real time? It all starts with what objective has been given here. So at the end once the objective is given to you, what you have to do ultimately you have to present it to others. Whatever you're analyzing, correcting and finding the solution for ultimately you have to tell that solution to others all the business process managers and the decision makers that is called as a storytelling that is called as a storytelling with the data or in a very simple layman language a PowerPoint presentation. Okay, it's a simple presentation but the way to give the presentation is like you're telling a story because mostly BPM CEOs, okay, they are not good with technical jargon. They do know their domain. They do have the domain knowledge and experience in that particular industry. But you cannot tell them this is a correlation, this is a chart. You cannot tell them that. You give them a proper narrative, a communication like telling a story. for example. Okay. So you have figured out uh you start with that this is the problem we were facing. So let's say you said that we are facing a problem where we were not able to we are not uh able to uh move we are not able to uh reduce the defects in the laptop and uh so far we had 10 uh on an average 10 defects per laptop. Out of these three defects were found in 80% of the laptops. So now I have figured out why those 80% laptops were happening either because of the vendor or because the employees were not properly trained well on how to use that particular robot. Right? So you will go ahead and you recommend solution and you tell them if we go ahead and uh talk to the vendor we can get that much refunded we can have the new uh vendor lined up and uh we will reduce the cost by that much. If we train the employees the cost is going to be that much that much dollars but in reducing the defects we will be recovering that cost in less than 3 months. So that's how you go ahead and you tell a story. You don't uh you use numbers inside that story but first you set the context. Without uh setting up the context all right there is no meaning to any meeting. Okay. You solve a problem on a certain domain. You work on pharmacy, you work in insurance, you work in BFSI, you work in uh product based company, you work in service based company. Every industry is separate. That's why you have MBAs to figure out and how to approach and solve a problem. That's theory. So it comes with your theoretical knowledge. You all have done your graduations and postgraduations, right? You know how your industry works. Most of you are working professionals. So you learn that MBA management knowledge and how to approach a solution and solve a problem. Here we are for technical training. Since we are here for technical training, we will be learning about how to create charts, how to use Tableau properly to analyze your data set. What which data set is there? Do you understand your data set or not? This comes from your own graduation and postgraduation and what you have learned there. For example, everyone working in pharmacy and healthcare. Okay. If I give clinical data to you, do you and you look at that data that how does this particular uh uh drug is working out. So let's say there is a new drug out in the market. They have tested that on uh certain groups and now that data is up to you to analyze. So everyone working in pharma in and in healthcare industry will you understand that data? Yes or no? Their bio their bio stats and uh if you work in pharmacy and healthcare, will you understand the clinical data? Yes or no? If you work in pharmacy and healthcare, then you understand the jargon, you understand the terminology, you understand what does uh certain uh readings uh bio readings mean. But if I'm from finance and I give that data to you that see this is clinical data this is the bio readings of a certain human being will we understand that? No. So that's the logic of solving and approaching the solution. You have to have the domain knowledge. That domain knowledge come from your own graduation and postgraduation or working in the industry. Are we good sahil? We'll only learn uh how to technically use the tableau. But in Tableau there is uh one place of creating PowerPoint and that's where you will learn uh about uh telling a story and creating a story board effectively that what should come first in a story, what should come later in a story. So basically first we'll have our problem right how we uh the uh statistics or the numbers we have used to analyze what happened where and then we recommend a solution. Right? So basically we understand the context and we saw and accordingly we talk through the story that's why this topic is here. Okay. So we communicate properly so that we can have proper outcomes and this is what we find out that is storytelling. Now next here is introduction. I'll tell you a very real scenario guys. Okay let's understand a very very real scenario. Let's say you work in Bosch India for example. In Bosch India, you are uh you are the floor manager. Okay. You have been tasked with to figure out how to move the vehicles in a uh in the shortest route from warehouse one to warehouse 2 to pick out certain parts of a huge engine or machines. So you are the one who is tasked to find out what is causing delays when they are transferring uh the unfinished parts or the uh raw material from here and there. This is actually the real problem. Now tell me from where do you collect the data for this problem? Yes, you are correct. Data gives only facts. Context will give the meaning to the problem statement. And to know where to get the data. Now in this scenario, tell me you're standing in a production plant. We've all seen factories from the outside and maybe from the inside. How will you figure that out? From where will you get that data? First you have to go to the HR, right? And get all the staff who is running those uh uh vehicles. Then you will go to the production plant manager. You'll ask that how many how many vehicles do we have? You should have the entire layout. So you go to the person who handles the layout, the engineers and the architectures architects out out there who will manage the entire layout. Then you go to the store manager who will takes care of the store. You have to go ahead and talk to 10 to 15 different teams and departments. Email them in uh email them to please give me the data. please give me the data and trust me 80% of your time will go only in collecting your data and they will give take 6 to 7 months just to give you the data and this is the real scenario I'm talking about this happens in projects when we do it so when you kick starting any project for data collection your first time implementing analysis somewhere right this is how it actually goes on the ground let's get introduced to Tableau everyone this is what we are here for. Now Tableau is uh not just a visualization software. It's a a proper business intelligence software. So currently we are going to work with Tableau public. It helps us of course and importing the data set and uh analyzing the data set and create reports and graphs out of it. Right? Of course it can handle large amount of data set. The best part about Tableau is mostly things is on drag and drop basis. There are custom visualizations provided to us. In professional version, you can connect with 75 plus data sources and it provides a very unique view uh unique way to combine data set coming from multiple data sources. So when we reach to the data connections, we will discuss about that technically in detail. Now we are going to go ahead and understand what we are going to work within Tableau. Now when I say Tableau is a business intelligence tool here. So Tableau uh or Salesforce okay within Tableau provides us with many different uh products out there. First product they provide us with Tableau Prep Builder. Tableau Prep Builder is an entirely separate application everyone uh separate software. It is used specifically only for data preparation. Data preparation means Tableau pre builder helps us to extract data from any other source like Excel, CSV, JSON or any other Oracle or any other SQL database or any other cloud out there. Right? So it will extract data from there. It will transform data, clean data. It will transform and clean data for us. And from here then we get to load it to uh load it to another tableau applications. For example, we can clean the data and load it directly to the server. So now we have a clean data into the server. Okay. So it can be either a Tableau server or Tableau online cloud. Any one of these can be used by the uh by the organization. It can be in-house server within their premises on premise server or it can be online it means it's a cloud. Okay. So if this clean data is saved into the server from the server it will not only save the data it also enable us to share it across multiple users. Same as you have Google drive, one drive. We have all used Google drive and one drive. Everyone we all understand what a cloud and a server is. Yes or no please. Yes, very good. In the similar manner they provide us Tableau server. Tableau server is not as advanced as PowerBI server. Those who know about PowerBI, it is not as advanced as PowerBI service. It is very simple like Google Drive and one drive. You share it across the people and that's it. Uh another way is that we can load it directly into Tableau Professional desktop. When I say Tableau Professional Desktop, it means it's a uh professional desktop. It means it's a paid software. Okay, license is paid. It's a paid software. It is only available for us to view for 14 days trial and then you cannot renew it. It is not renewable and it is majorly provided by the organizations only. And Tableau prep builder only connects to Tableau Professional desktop. The Tableau professional desktop here is used for designing and developing. Design and development of reports. Design and development of reports. Creating report. Creating visualizations. Right? So all the three environments are here. This is where we do the data analysis. Okay. Designing our analysis here. And what we will be using then what we will be using then to learn Tableau we will be utilizing Tableau public desktop everyone. Why Tableau public desktop? Because it is free forever and plus it uh holds all the updates. All the new updates are always here. Okay. It is always updated and always free. always updated and always free. All right. That means can we use this tool for data governance instead of our programming? No. Our programming is pure pure statistics and machine learning application. Right? And since you are doing the machine learning there, it is recommended that you do the basic data preparation there itself. However, if you want to clean your data from here and then feed it into there, that's a different part. But yes once you uh have our programming for huge data also you can use it. It has got no limit of how much data you can use or huge data also you can use it. You can even uh go ahead and uh combine R and Tableau together. Right. So are in Tableau Professional or the Tableau public? So everyone we are going to use the Tableau public here. Of course we have another uh product uh given here. This is just to view for example now you have cleaned the data you have uh went ahead and created the reports and visualizations here. Of course you'll share it again to the server and from the server it is uh shared with multiple employees who are intended to see that particular charts and reports. Now where are where where these employees will view that report either in their laptops or in their tabs and mobiles. So they provide only viewing applications like Tableau reader and Tableau mobile. So these are the different Tableau products and we will be working on this one. We'll be working only on Tableau public desktop. Are we clear? All right. So remember that we are going to use the free version here. There are many calculations there. It's all based on from where are you getting the data and there are no calculations. There is a language that can be used. You can use SQL inside Tableau. You can use Python inside Tableau just to get your data. It is all based on from which place you are extracting the data. Right. So everyone let's understand here Tableau public here is is a free application. Right. So there are few things that you should know about the Tableau public. So let's here of course we know it's a free license but since it's free here okay we can only go ahead and get uh a limited range of file and data connectors. Data connectors means from where I can get the files. So we can only get the files that are saved in our system like Excel and CSV or JSON. These are the extension of files that we can extract here. Or if you're working in Windows, you can get excess files too or any other database files within your system. And you can also get any kind of online free online that doesn't require any login ID, password. All right. uh website data which doesn't require any online password or uh a specific extraction of data. So those kind of limited range of files we can get here but of uh but of course if uh it's uh proper professional desktop right we have 90 plus data connectors you can connect with. Now within Tableau public the most important part here is that you uh you cannot have data with more than 1 million rows in professional version of course you have unlimited storage and Tableau public you constantly need internet connection uh for Tableau desktop you don't need internet connection okay you can still save the file here right now and let's understand one thing uh here very very important Here everyone please remember since it is Tableau public right and it is not allowing us to uh it is not giving us and allowing us to use any online data. Please be assured that you are not supposed to use any type of personal data or any type of u uh your organization's data here because this Tableau public do not provide you any privacy or security because it is Tableau public. It is only meant for uh your learning Tableau purposes and please only use the data which is publicly provided either for training purposes or a government or the data sources provided it for public use. So on GitHub there are many data set that are given for public. All right. Uh many governments give data out for public. Uh so use that use those type of data set. Please do not ever ever use your personal data or your organization's data not even for the practice. Please don't do that. It is not secured. You will because it operates on the server. Plus it does not provide any integration with any other Tableau product like Tableau Prep, Tableau Server or anything else. It works on public server. Tableau public server. So do not use your own or your organizational data set here. So right now we are at the Tableau interface here and this is where we see the connect pen. So these are called as sections. This is you can say connect section. All right. Uh in the open section you will see your recent files you're currently working with. And this here is called as discover section. Right. Why it is called as a discover section? Because this third discover section takes you to uh outside blogs of Tableau. Learn how to learn videos and uh famous visualization created by Tableau public and more and many blogs written by using that or any new updates are there that will be written here. So in the connect section here okay of first it's just telling us we are we're in Tableau public and these are different files we can connect with here we are at server what server we can connect with here nothing much that's the online data any data which is online and does not require any a login now you must be thinking how Google drive because your Google drive to connect with Google drive here okay you uh might not need a login. It is a publicly available data set. So this is how we can go ahead and connect within Tableau here. So these are the three sections, first three sections here. Okay. So this is a text file, comma, separated values. It's a text file everyone. So the second option is the text file. We click on the second option text file here. After clicking on text file, a dialog box opens up. A dialog box opens up here. Once the dialog box opens up, go ahead and find where your file is. Wherever you have saved it, go ahead and find that file. Okay. Once you find that file, you select the file and you click okay. So follow along with me right now. That's a very small operation that we are going to do. First go to the text file. Go ahead click on that. Once you click on the text file, a dialog box appears. In this dialogue box, go ahead and find out where your employee database is. Once you found the employee database, select that and click open. And when you click open, try to explain in words what are you looking at. Okay? Try to explain in words what are you looking at here. Okay? Hi. Okay. All right. So, uh I will go ahead and explain this again. Every from now on we are uh going ahead and going to see technical steps. As I've told you before the break first I will show you what to do. I will explicitly will tell you that now follow along then you follow along. All right. First please see and observe. Okay. Are we good? And this applies to everything that is going to come forward. Okay. So now follow along with me. I have already shown twice. Now follow along with me We click on text file. The second option. The dialog box opens up. In this dialogue box go ahead and find where your employee databases that I have shared. Once you find employee database CSV, you select it wherever you find it and you click on open. Right? So go ahead click on open everyone. Once you click on open, whatever you're looking at your screen, try to explain in words what are you looking at. This is a very very important skill you need to have if you work in analysis. The communication part explain what are you looking at after clicking on open. I'll be waiting for your messages here. Employee details. What else? What else do you see on the screen after clicking on open? Yes, correct. List of files and blank screen. A grandma, you're seeing list of files on left and blank main screen. Have you clicked on text file? Yes correct Adish. So see this is what should happen here. Yes correct. When you click on open first we will see and observe. Okay let's see and observe. Whenever we whenever you are learning a new software you always start from the leftand upper corner. On leftand upper corner you can see here right now we have file data window. So we have menu systems here. Okay, these are called as menu bars. Menu drop-downs. Below the menu dropdowns here we have quick access toolbar. Undo, redo buttons are there, save, refresh buttons are here. Now where are we at? So you can clearly see here we are at data source window. Look at the left hand bottom corner everyone. What is written here? Currently we are at data source window of Tableau. Currently we are only seeing and observing. Yes, it says data source. It says data source here. Now look at this section here. Do you see this is a separate section? It says connections. This connections here is only saving the file path. This connections here is only saving the file path that where does this particular data lies? That's it. It is not saving anything else. Okay, it is not saving anything else. See when you right click on that, it will simply ask for edit connection. Edit connection means the file path that where this file path resides. Now wherever this file resides inside your system in that particular folder how many text files you have here? How many text files you have here? So how many of you are looking at multiple CSV files here listed out is relator right? If you're looking at multiple CSV files here because in that particular folder you have multiple CSV files inside it. So if you have uh if you want to work with multiple CSV files you can just keep them in a folder and extract one of them here. Yeah, it's fine. Surya. Yes. So why do I have multiple CSV files? Because at this file path inside that folder there are multiple CSV files here. That's why all are listed out. However, no matter how many files you have here in the white space, you will only have employee database. Do you only have employee database? Now, uh this here is your data source window. Okay, this is called as logical layer. This is called as logical layer. There's a reason we call it like that. So, we'll get into that later. But this is your logical layer of data source window. If you keep your data here, it means Tableau is reading your data. Tableau reads your data here. Okay? Tableau reads your data here. Now, no matter from where you're getting your data, please remember that we are in Tableau public. Tableau public connects only with the local system files saved within your system. Surya only Tableau professional version will help you to connect directly with the databases. And within Tableau here we are in within Tableau public also we are going to learn how to create a database how to work with multiple files but as in when we reach to the topic. Okay. So once your data is here and everyone once you can see the preview of your data preview of your data here it means your Tableau is now connected to data and you can analyze the data. So right now how many rows and columns does this data set have? How many rows and columns does this data set have? Everyone, can you find this out? Right. So, it says here 12 fields and 20 rows. Fields here means columns everyone. Okay. Sometimes this is also called as attributes. And rows are rows, right? Rows are rows. Sometime rows are also called as records. So we have got 12 columns and 20 12 columns and 20 rows. Very good. Currently we are able to see all the 20 rows of data set here. Right. So this part here is showing us data preview. And on the left hand side here this window is called as metadata. Metadata means information about data. Information about data. What kind of information about data? And remember this metadata window will keep on changing. Right now we are at CSV. So what kind of information it is giving us here? Read field name is employee ID. Remove field name is employee ID. What does that mean? It means that inside the CSV file, the original, okay, the original CSV file, the the name was written in all caps, all uppercase letters. So what it does here is it has updated the field name within Tableau. So when in Tableau it has imported the data, right? So in Tableau in the imported data it has went ahead and have changed the name of the columns in the proper case. Do you see that? There is no underscore sign anymore. Just a spaces there. Do you see the differences? Yes or no? Please observe. Just observe. Great. So this is metadata window. It will keep on changing as in when we will keep bringing in new data and information. Great. So before we move forward here, let's understand how Tableau reads data set everyone. So observe just an observation here. Okay. Uh so we can uh see here this is employee ID. This is name, gender, role. All of this is uh text. All these are simple text everyone. Right? But as soon as we reach to experience here experience is a number. So go ahead and observe everyone on the uh left and upper corner of every column. Left and upper corner of every column there is some kind of symbol or icon there. Right? So go ahead and click on this pound sign here above the experience. If you will click on this pound sign here above the experience, you will see the list of data type that Tableau can identify and work with you will find number, decimal, whole number, date and time, a string means text or character or there are many geographical roles that Tableau is known for. Tableau is majorly known for its geographical roles. It can even identify a individual street and a building. Okay. So it is quite uh and it has demographic uh stats already embedded in it. So yes it is meant for it geographical roles. So go ahead. All right. Click you can either click on ABC and you can see all of them here. You can also go ahead and click on uh the pound sign and see all the roles No because sur your column will contain the date and time. So let's say it's a time sheet for all the employees when they have logged in today. So it will have date and time. So it will automatically identify that this particular column has data which is a number or which is a text or which uh represents date and time. So this is here are data types everyone. Data types means what type of data is stored inside column. Data type is telling the tableau what type of data is stored in that column. We are not calculating anything. It's just the data that is saved inside the column. Right? So there number, date and text. Other are you can see it's a country. So it is giving it a globe icon because uh it's a country. It is a geographical location. Right? So inside this we are not calculating anything. These are just a geographical locations. These are just numbers. This is a number. This is just a text an alpha numerical value. Okay. Are we good? Surya it automatically identifies if it is in a proper format. Either it is going to be DDMM Y format right or it is going to be mmd Y format or any format. It the moment it comes in this format it identifies automatically. Okay. In this case experience is just a round number an integer. So it is identifying that as an integer automatically right. All right everyone. So here we are. So right now we can see we have an employee data. We have their roles which department do they belong to and which country they work for for salary and their rating. All right. Thank you, Surya. Now, let's go ahead and click on sheet one. Let's go ahead and click on sheet one, everyone. When you click on sheet one, try to explain in words what are you looking at. Okay? Click on sheet one. Try to at. Sheet one is just towards the right of the data source. A blank sheet is there. Very good. On the right hand side you have many graphs there. Very good. What else? Column and row we see column names. Very good. Same column names are appearing on the left hand side. Yes, correct. Good observation there everyone. Very good. Very good everyone. Great. Format options. Some page and filters is also written there. Very good. Yes, analytics is there. Great. I'm glad to see the participation and the interaction and good observations everyone. So now let's understand the terminologies here. Okay. Uh hi Jika. Jikica are you a data source right now? Jikica, are you at data source? Right. So where uh do you see sheet one just towards the right of the data source here wonderful thank you sa everything is in your own time I'm I'm going to explain the entire interface to you'll get your answer okay all right everyone so let's go ahead and learn some terminologies here why because before we learn tableau we have to understand terminology technologies that Tableau follows up. So these here are called as menu drop-downs. These are specifically called as menu drop-downs or a drop-own menu because when you click on that, click on any one of these, okay, the related menu options will open up, related features options will open up. Below that here you have quick access toolbar. Quick access toolbar. All the tools that are already present in menu drop-down but these are frequently used tools. So these are all kept here on the On the right hand side here this is called as show me. Show me is a helper which help us to select the type of graph we are eligible to create. Now coming below here this is your data and analytics pane. What do we call this here? We call this pane. So this is data pane. This is analytics pane. Under the data pane right now under the data pane right now observe here that we can see all the names of columns here. But observe closely here when uh observe closely here when you are hovering the cursor over here. When you hover the cursor over here, first few names, do you see it is blue in color plus all the names inside the data pane right now are e are all ABC and you'll also find a very faint gray colored line here and below that faint gray colored line when you hover the cursor over that everything is green in color. And all our numbers employee rating, experience, salary. And here you can see all our numbers because it is uh bringing the uh pound sign here giving you uh the pound signs here in green color. Go ahead and observe that. Go ahead. Hover the cursor everyone and read the data type here. Are these all blue in color? Let me know. Just over no clicking. Just over the cursor. These blue colored column names are called as dimensions in tab. So when I will go ahead and ask you to go to dimensions, right? You go to dimensions. So what are dimensions? All everything that appears in blue color are dimensions. Everything that appears above this faint gray line. So there is a faint gray line here. Observe that everyone above this faint gray line all the blue color categorical variables appear. So what is blue color and dimensions here? All the categorical variables. Categorical variables means any variable which has name of anything. Name of a person, name of a place, name of a uh name of a product, name of a department, name of a road, name of a country, anything. Name of anything and anyone. Name of anything or anyone. That is your categorical variable. Okay, it should be name of something, name of something and or you have date and time. All of this is your dimensions. it will be automatically categorized and placed together. So all the blue ones are placed together. Now similarly here you have green ones employee rating, experience and salary. Till employee rating, experience and salary here all the green ones here are called as measures. All the green variables or green fields here are called as variables sorry called as measures. Measures these measures are numerical variables. These measures are numerical variables. Any kind of number an integer or a decimal or a float anything. All right. It will be green and measures. Okay. Now in this green and measures here you will see right now till here we are fine but below here everything is in italics and we don't we have not seen these names in the fields when we were in the Have you seen these names in the fields when we were looking at the data preview? Was there a column called as latitude or longitude? No. Because these here are autogenerated. Autogenerated measures. What is meant by autogenerated measures? Autogenerated measures are the measures which will be generated by Tableau based on data set. If Tableau can read the country and content continent name here, it will automatically bring the related latitude and longitude here. So that later on if we create a geographical map, we will be going ahead uh we can go ahead and create a proper geographical representation. Right? Now other than these other than these here observe that here you have two more things. One more in italics written as measure names. Another italics and written as measure values. Right? About measure names and measure values. They collectively keep the name of all the measures saved here. So the name of measures are saved inside this and all the values of measures are saved inside this. So this is technical part of Tableau as in when we move forward we'll understand about these two here. For now focus on everything blue is called as dimension. Everything green is called as measures. Okay Gory. Okay everyone, you got your answer Gori. Yes. Now why I'm emphasizing on these terminologies here? Let's please understand. Okay. These all are categorical values. And you are right Surya. You can call them a text. You can call them a character also. Okay. But problem here is that Tableau is the product of Salesforce, right? So they name it as a string. They name the text as a string. They cannot name that as a text data type because uh Microsoft called it as a text data type. So they are here calling it a string. They will make sure the terminologies are different than what has been followed there. Okay, just because the companies are different and they want to position their product as different. Are we clear? That's why we have to learn terminology because in their examinations for certification ETA, right? They will use only these terminologies to represent anything. Are we clear about the semantics of market everyone? That's why we have to learn individual terminology separately. Do we understand this? So please remember these are called as dimension always blue in color these are green they are always called as measure. So when I say go to dimensions you go to the blue colored ones when I say go to measures you go to green colored ones. Okay. All right. So we are moving forward then this here this white space here is this white space here is called as canvas. Everyone this canvas here, this canvas here, okay, can have only one type of chart. It can have only one type of chart. Meaning one sheet, one canvas and only one chart. Okay, if you work in Excel, you know you can create multiple charts in one place. If you work in PowerBI, Clicksense, you can create multiple charts at one place. And Tableau, one sheet has only one chart. And the best part about this here is you can switch off the show me dropdown. See you can switch it off. If you switch it off, you get better space to work with. And whatever terminologies I'm telling you here, it is all in the lesson two PowerPoint instructor slides. All the terminology terminologies are already there with the definition and we'll go through that also. Don't worry, Karthik. So this is called as canvas everyone. Just above the canvas, do you see the sheet one is written here? Okay, this is a separate box chart title. This is a separate box chart title. And above this we have column, rows, pages, filters. Right? All these four are called as shelf. So this is column shelf. This is rows shelf. This is pages shelf. This is filters shelf. So these are called as shelf. Okay. You can these are called as shelf. This here this here is the most important part of Tableau. This is the heart of Tableau. This is the heart of Tableau. Why? Because even show me which is uh a uh which is uh supposed to direct you on what to create it also uses this particular card. So we call this a marks card. Why are we calling it a card here? Because inside this card we decide the shape of the data point. See in the automatic drop-down we have multiple shapes that we can give and in then we go ahead and decide with color card that what should be the color we should uh color we should be giving out what should be the size of the shape what text should be written on the shape what more details I need to add any kind of tool tip we want to add and there are more cards that will keep reappearing here based on the type of the shape we selected So go to the marks card everyone. Click on this drop-down and just observe the different type of shapes that you can give here. Just observe. Don't change anything. Just observe the different type of shapes. Remember that if you will master this marks card, if you know how to use this marks card properly with columns and row shelf, you can create whatever shape you want here. And this is what we will focus on technically. You should know how to utilize this card properly. So go ahead click on the drop-own observe and let me know are you able to see all the shapes there? We are going to see that Laxmi don't worry still Laxmi. We are going to see that that why it says automatic. Let's see. So first thing everyone go ahead and understand how this rows and column works because this rows and columns shelf will help us to place and create a chart. Okay. So go ahead and remember that first whenever we want to check a default condition since we are new to Tableau right we want to understand what happens by default. So whenever you want to see the default reaction or default placement of things here, we will double click on that. Okay, we will double click on that. We do drag and drop. We do drag and drop. Okay, for custom placement for custom placement that I we want to decide where I want to place in which card. So for understanding default placement here, go to department and double click on department. Everyone go ahead and double click on department and tell me where does it go. Very good. When you double click here, when you double click here, your department is going into rows, right? So when your department is added into the rows here everyone how department is written on the canvas top to bottom the list of all the departments is written top to bottom. Yes it is written in top to bottom. Now go ahead and now drag and drop department into the columns. Go ahead and drag and drop the department into the column, please. And tell me what do you see? Drag and drop. Everyone drag and drop. Now we are seeing them as columns. Right? Now do you understand the difference here? What happened right? So if you're keeping it in columns here it is appearing as individual columns. It is appearing as individual columns when these were in rows. All right. It was appearing as individual rows. Individual rows. Yes. Very good. Now go ahead. Now go ahead and double click. Now go ahead and doubleclick on salary everyone. Now go ahead and double click on salary. So department remains in columns where okay you double click on salary and now tell me where does where salary is added by default. Can you be more specific? It is in the marks but in marks there are several cards right in which card it is uh there and you double clicked on salary where is it getting added? When you double click on it, all right, it will go to the text card. How do we know that? See the symbol here is very similar. Match the symbol everyone. Bhagri Sri Lakshmi. Are you able to see it now? It is in the marks and it is under the Got it. Yes. Very good. And look at the canvas right now. Look at the canvas right now. Everything is written uh now in this is column wise. It is written column wise everything and the numbers appear right Also observe it is giving you sum of salary. Meaning it is adding up salary for each and every department here. Correct. Observe here this says sum of salary. Does it say sum of salary here? No. But as soon as you bring salary onto the canvas as per the department it is adding up the salary creating the report as we created in the example when we started the session. So we have a report everyone yes or no remember that do we understand the report has been created an aggregated This is an aggregated report everyone. this is a report that we have to visualize. Correct? This is a report that we need to visualize. That's what data visualization is. So go ahead, grab your sum of salary from the marks card and drop it into the rows and tell me what do you see on your screens. Pick up your sab of salary, drop it, drag it and drop it into the rows everyone and tell me what do you see on your screen. Is it a horizontal or vertical? I'll also go ahead and uh bring it here. It's a vertical bar chart. It's a vertical bar chart. So someone has asked me what is automatic right. So automatic here is the automatic selection of the chart based on which dimension and measure you are adding up in the canvas. Right? So based on how many measures and how many dimensions you are placing on the canvas on based on that it will pick up the chart for you here. Now let's uh observe something fantastic about Tableau and the canvas. All right. Which axis is this everyone? Which which is this axis here? This horizontal x-axis. This is horizontal x-axis. And this here is horizontal y-axis. Sorry, vertical yaxis. This is vertical y-axis. Here this is vertical y-axis. Observe here when you are bringing columns uh when you are bringing department into the columns shelf where department is placed X or Y axis where is department X or Y axis everyone very good it is on the X axis horizontal axis Very good. About sum of salary. Where is sum of salary? In which x is sum of salary is because we have placed it in the rows y-axis vertical axis. So if you place anything in columns it get placed into X-axis. If you place anything in rows it get placed into Yaxis. Clear? Clear how we are creating the charts Just to keep keep this in memory forever. Go ahead and find a simple icon here looking like this. Just above the pages card, find a icon looking like this and click on this. This is your swap access. This is your swap access icon. Go ahead and find this icon everyone. It is near the sort icons here above the pages card or and above the columns here. Go ahead and click on it and tell me what do you see now. swapped. Very good. Go ahead and find this. I hope everyone is able to find this. Yes. Very good, Jodica. So, observe everyone. When you click on this swap right now, what happens? It has simply changed the rows in uh salary into the columns and department into the rows. That's it. That's what happened, right? So swap and now what we have is a simple uh horizontal bar chart. So now on the y-axis we have department on the x-axis now we have salary. Yes. So graph will change according to what we choose to place in rows and columns. So now let's go ahead and uh can you look at this now? Why we were creating charts? Why we did we converted that report into a visualization so that we can identify a pattern we can read the report uh better correct? So go ahead look at this chart here and tell me which department has highest salary given. Which department is getting the highest salary and how much is it? Right. So when I asked you about how much is it, we are trying to make some sense out of it by uh trying to measure it up to the excess here somewhere above 40k. Right? Some of you went ahead and you hovered the cursor over it and in the small box which is called as a tool tip 41800 is appearing here. Now just imagine you have created this chart. You share this chart with your manager and will you would you like to add a note in the email saying that if you want to know the number exact number calculated hover over each bar to know the number. Does that sound right? No we cannot do that. Okay, we are creating this here so that they can understand the chart better, right? So we need to write the numbers. These numbers in Tableau are called as mark label. In Microsoft we call them data label. So how do we add that? So there is a T inside the square. Go ahead and switch it on. Remember that in Tableau we call them mark label. In Microsoft we call them data labels. Okay. So go ahead and switch it on everyone. Now when you switch this labels on I am sure in few of you you are not able to see alternate numbers. You're not able to see alternate numbers in few of your laptop screens. Since you might not be able to see alternate numbers, go ahead find t inside the square. Switch it on. Just click on that and let me know are all of you are able to see all the numbers here or few numbers are missing from between alternate number is not showing in few of them will happen. Why? It is based on the laptop screen size and how much resolution of is there. So few will sometimes few will be missing. Sometimes you will be able to see everything. So what should we do then? So let's understand here. Remember uh I have told you the canvas can have only one chart. So let's use the entire space. Why to uh leave this space blank to use this entire space everyone? from where you have managed to get the labels towards the right hand side of that there is a drop-down called as a standard. So go to find as a standard drop-down here on quick access toolbar and on this drop-down select entire view. Go to that drop-down and select entire view everyone. Great. Now can you tell me uh the department which is getting the lowest salary? Tell me department getting the lowest salary. Right. Yes. So when I asked you right now that which particular one is getting the lowest salary ma okay as a human being okay as a human being what did you what did you uh do here your eyes here it started to compare the length of every bar right since you already knew retail is the highest you have left that out and then you compared the length of every bar and then you reached here as a human being that's what you did Right? So it took a few seconds uh to answer. It took few seconds for you to answer. The answer was not immediate. That is why we can go ahead and sort. So the end user if they want to go ahead and immediately want to see the lowest and highest they don't have to find it out. So go ahead and sort it out everyone. So just before the t inside the square and entire view towards the right of them you will find the sorting. So there is an ascending one, there is a descending one. You can decide what to keep first. Now you don't. Now if I ask you give me the second highest, give me the second highest answer is quick. Give me the second lowest answer is quick. Yes, absolutely right everyone. Automative and healthcare correct. So see now the answer was quick. Now you now you didn't even you are not even looking at the right hand side right you didn't even look at that you just looked at this that oh this is uh ascending or descending this is my answer so this is how visualizations are formatted and created to make sure everything works right so our first visual uh our first visual is done everyone we created our first visualization here let's go ahead and Rename the sheet. Let's rename the sheet here. This says salary by department. How do we rename this sheet? So go to the leftand bottom corner. Sheet one is written here. You can right click on it and rename or same as Excel you can double click on it and rename. All right. So go ahead and rename the sheet at the bottom everyone. I'm going to rename this as salary by department. Once you have named it, let me know. Do you see any difference on your chart or on your interface anywhere? Yes, very good. You'll realize that once you have named the sheet here, the chart title is automatically updated. So now, now let's understand everyone here. Okay, how does uh this is working? How uh it is getting updated by itself? To understand this title here, just go ahead and double click on the title Go ahead and double click on the title. When you double click on the title everyone, do you have a dialog box like this? Now read the name of the dialog box. What is the name of the dialog box? No matter in which tool you work with, every dialogue box or pop-up box is going to have some name. Okay. So this says edit title and inside the edit title is it writing salary by department here. Is this writing the name that we have written here? No. It is going ahead and writing sheet name inside the angular bracket. Inside the angular bracket. So remember that in Tableau whenever you see anything written within these angular brackets it means that it is reference to some value. it is reference to some value. It can be reference to sheet name, page name, uh to a certain dimension or a measure and any other object. So whenever you see these kind of uh brackets, angular brackets, it means it is referring to something. So currently the reference was sheet name. So whatever you write in the sheet name will appear here. However, if you want to write by your own, you can do that too. If you want to delete that, you can do that too. As we are learning the basics today, we will simply go ahead and understand how do I format the sheet name because sheet name is perfect. But if we want to format this, how do we do that? So if you keep your cursor inside and you change anything here, it won't reflect on it. To make changes in this here, you have to select the entire part. When you select the entire part with control A or drag and drop, right, it will highlight in blue color. Once you select all, it highlights in blue color. Then you can go ahead and make changes. Make changes like you can make change in type of font. You can make changes in type of font size. You can bold it. You want to change the color, you can do that too. You can also go ahead and make it at the center. When you do any of these changes here and you click on apply, apply, it shows the preview here. If you're happy with the preview, you can click okay. If not, you can reset it back. All right. So, follow along with me right now. Go ahead and double click. You are you are already inside. Right. Now go ahead and either you use Ctrl A or you simply drag drop and select select like this. After selecting the name like this it says Tableauite by default. So this is your font styles everyone. You can click on the drop down here and change the font styles any font styles from here. Okay. Select any font style that you like. Now this is your font size. In this font size here, this is too big. You can go ahead and decide uh 12 for example. Now we can bold it. If you want to change it some color around here, you can change the color around here. This is alignment everyone. See? So let's say I'm aligning it at the center and then click on apply and look at the So apply button shows the preview. If you like the preview, good. If you don't like the preview, you want to change the color or something, do that. Click on apply again. See the preview. Once you're happy, you can click on okay. All right. So right now we have created one chart here everyone. Now, how do we create another chart? To create another chart here, we need to add one more sheet. How do we add a one more sheet, everyone? There are two ways to do it. Do you see there is a plus sign here? Do you see there's a plus sign here? Right? And but there are three types of plus signs. And we have a plus sign here also. Here also also there is a plus sign. So go ahead to this drop-down here and see all the three options. First we see and observe right read all the three options here. It says new worksheet, new dashboard, new story. New worksheet is the exact same sheet that we are working in. When we have enough worksheets and enough charts that we can create a dashboard out of it, we add the dashboard. And when we have enough worksheets, dashboards and our entire presentation is prepared that yes, I have all the material for my presentation. I've got this pro solution to the problem, we go ahead and we add a story. So all these three are very different interfaces. For now, we need work eat. Okay, shortcut key is also written there. So for now we need new worksheet everyone. So go to the drop-down and click on new worksheet. You will see another sheet is added up with uh name sheet 2 and the exact same interface is there. Yes. Yes. Wonderful. Now let's go ahead and bring let's go ahead and now this time we drag and drop. Uh now go ahead and double click on gender. Everyone go ahead and double click on gender and then double click on employee DB. CSV count the italics one and double click on employee DB dot CSV italics one counts how many yes right counts the how many uh employees are there based on gender great now what is the best way to represent these numbers instead of giving the numbers will it be better if we represent this in percentage that how in the percentage uh contribution is there. We usually see that in a percentage, right? So, first we go ahead and calculate percentage. Yes, that's where we are headed digit. So, everyone go to this count under the marks card, green colored count here. Right click on that count. Hi Manav. Uh last step was double click on this italics count. So double click on gender and double click on this count italics count. That was the last step. You were not there at sheet two. We go to this plus sign and new worksheet manav or we can also click on this plus sign here. The first plus sign or simplrm. So we are adding a sheet. Are we here at the add a sheet? Great. So now double click on gender. Double click on employee. And when the employee gets added into the text card on double click, we right click on it. We go to quick table calculation and click on percent of total everyone. Do you have percentage written there in front of you everyone? Yes. Mav are we on the same page now? You made a mistake somewhere. It's okay. No worries. uh we are about I'm about to conclude the session one of so once I conclude the session I will let you share the screen I have one more learner uh uh where I have to see and solve the doubt all right no worries right so now uh how do we represent percentage everyone with a pie chart right so let's go ahead and go to show me and click on the pie chart go to show me and click on the pie chart everyone Click on show me and the pie chart. Is this the pie chart you were expecting out of Tableau? Everyone go to show me on the second row you will find pie chart. Do you have a pie chart? Uh uh as I have told before okay we go to this green colored one. We right click on this count under the marks card. We go to quick table and we click on percent of total. Right click on that quick table calculation percent of total. Now go to show me and click on pie chart everyone. Now pie chart looks like this. Okay. But it looks like a small sticker. So go ahead and switch on label everyone and view this in the standard view entire view. Okay. Okay. So, simply switch on the labels, go to the drop-down and view it in the entire view. Are we good? So, first we clicked on pie chart. Then we switched on the labels. Then we switched on the entire view. Yes, better. Now it will be much better if you will go ahead and switch off the show me. So switch show me is just a drop down. So everyone collapse the show me. Please collapse the show me. The moment you will click on show me and it collapses. You will see legends here. It will tell you which color is F, which color is M. So now it is easier for you to go ahead and understand what's going on. Right? That which color is what. So that on the right hand uh upper corner, you will find legend. Right? So in the when you create a pie chart, you will be able to see the legend here. Legend is telling us which color meaning what. Are we all able to see this? So now let's go ahead and save our work. Everyone go to the file dropdown and save your work. So go ahead file and save as within your system. Please go to file and save as. Please. Okay. when you're saving your workbook. Okay, please remember to save aswbx. Save as type should be twwbx. Why it has to be that? I will explain you tomorrow. But please make sure that when you're saving it right, you save it as TWWBX. So today we'll go ahead and uh import the data from an Excel workbook. After importing data from the Excel workbook, we are going to move forward and create different type of charts. We will deep dive into dimension versus We will also go ahead and learn about how does date behave uh in Tableau. Then we will go ahead after creating multiple charts we will also go ahead and add a dashboard. Today we'll understand about dashboard. After dashboard we'll go ahead and create a story board also everyone. We'll go ahead and create a story too. So we're going to see basic different type of charts Quantitative used to categorize the data. Qualitative surya qualitative. Let me show you uh guys again. And tan do you use numerical also numerical values to create a chart too? Does it define what a dimension is? You can define numerical also like that that I used to create the charts. There are type of charts that are created only by numerical variables. No categorical variable required. Read this again Dimensions are qualitative. Qualitative. Quality. Numericals are quantitative. Quantity that represents quantity that represents quality. Yeah. Yeah, it's fine. Right. Clear. All right. So, uh this was the today's agenda everyone. So, we are going to create multiple different type of charts. First thing we connect with Excel and then we go ahead and create charts out of that. Yes. All right. So, I'm going to reshare the screen again and everyone please go ahead and open up uh Tableau workbook from your desktop. A blank Tableau workbook from the desktop. Once you are here, you will be able to see the day one CSV file if you have saved it in your system. You will see the uh tile here. So everyone, let's go ahead and connect with Excel right now. So Excel is the first one here, Microsoft Excel. Yes, I would like to remind you one more thing here. All these steps that we have done before, okay, is steps which are repetitive which we have done already before or in the previous day. So repetitive steps here you will follow along with me you will follow along with me like connecting with data set you know how to do that okay so you will follow along with me and when we come across new steps all right and I will specifically ask you to only see and observe please do not follow okay whenever the new steps will arrive I will ask you to see and observe you will only see and observe all right then I will repeat these steps after clearing everything. That's when you're supposed to follow. Just a reminder to everyone. In case you still miss, all right? In case you still miss uh these steps, ask immediately. Okay? Don't wait uh for uh entire thing to be over. Just ask immediately. If it is possible, of course, I'll go ahead and repeat it for you. Otherwise, I will ask you to share the screen accordingly. Okay? All right. So let's start working. So everyone let's go ahead click on Microsoft Excel. This is the first option here. Go ahead and find your sample super store. Sample super store 2 and click on open. This you can do. We have done this before. Now once we click on open remember we are in the data source. We are at the data source right now. Now in the data source right now it is empty. Yesterday we can see the preview automatically remember. So currently let's understand what is happening here. Let's understand what what happened here. So this connection here is taking it to the folder or the file path. Now inside this file path it uh here Tableau is informing us that I am connected to this Excel workbook. I'm connected to this Excel workbook and inside that Excel workbook there are three sheets and other objects are Okay, because the icon is different. So other than these three sheets other Excel objects are also here. Now it is up to us to decide what should be read by Tableau. So whatever you will drag and drop here only that data is read by Taboo only that data. So if nothing is here Taboo is not reading anything right. So we want it to read the orders data only for now. So go ahead. You can either doubleclick or you can drag and drop here or so you either double click on it or you drag and drop it. Do any one of the two things everyone. either double click on it or drag and drop. Once you drag and drop, tell me how many rows and columns are here. Just double click or drag and drop. Very good. So, right now we have 21 fields and more than 10,000 rows. Very Yes. Great. Now tell me here how many rows are you able to see in the preview? Column do you repeat? Uh column could you repeat? Uh hi Kavita are you here? All right so are you here? Were you connected to Excel? Right. So, next part that you have to do is you can uh do you see order people and returns here? Listed out. Just drag and drop orders here in the white space. Just drag and drop orders here and you will be able to see the data preview. So everyone let's go ahead and see right now how many rows you are actually able to see right now how many rows you're actually able to see only 100 yesterday when you connected to CSV there were 20 rows right and you were able to see all 20 rows here and you were able to see all the 20 rows now we have only 100 rows why because it is just the preview of the data set. It is just a preview of the data set that how it is there. However, you can choose how many rows you want. If you go to this 100 rows here and you type five, you will see only first five rows. Type five and you will see only first five rows. So, it depends on you how much preview do you want to see. You want to see thousand rows, you want to see 100 rows, 50 rows, it's all up to you. It is only for you to understand how it works. So go to the 100 everyone. All right. So for you it is 100. So go to this 100 here. Delete that 100 and type five and you will see the five rows. But convert it back to 100. Type five. Press enter. You will be able to see only first five rows. Once you see that, please convert it back to 100. Go inside it again, type 100 again and press enter. Once you're back to 100 and you have pressed enter. All right, everyone. So before we go ahead and start analyzing this data set, we have to understand the data set here because there are 21 columns. So let's go ahead and collapse the metadata, please. Let's collapse the metadata here and let's see what this data set is all about. So we have here row ID, we have order ID, order date, shipping date. So here we have uh individual orders by which mode they are shipped. So this all here is the order details everyone. ID, order date, ship date all our order details. Right? Now if you move forward here uh we move forward here. Now we have customer ID, customer name, segment and which particular location do they belong to. So here these are customer details. Which type of customer segment they fall in and when we scroll towards here now we have location detail till the postal code and region. And then we have product detail that what was the product ID, category, subcategory, name of the product, what they have boughten. And at the end here now we get the fact details meaning number details. What is the total sales, quantity they have ordered, any discount given and what was the profit gained out of each order ID or each transaction. So this kind of data is called as transactional data. Okay, this is your transactional data set which is giving you each an individual transaction. Now in this each and individual transaction here I want you to look at order ID and tell me is order ID unique or duplicate. Is it unique or duplicate? order ID because uh this identifies the individual order and transaction. It should be unique. But is it unique? You're right. It should be unique what we know here. But is it unique? No. We have duplicates here. Right? We can see 26 26 26 999. If I scroll down, there are more duplicates. See 99.999 then more 99.999. Same same order ID. Why do you think we have duplicates? Look at the data set. For example, this 126 126 is duplicate, Same customer can give multiple orders. That is clear. But order number will be different for that. Yes, but each order number is different. You also give online orders, right? So, every order number is different. Yes. Very good, Pratty. So, let's see here. everyone. So see here these are the repeated order ids right same uh date uh same person all right of course the same address same address but when you come to the product here you will realize that within that one single order they have ordered three separate products three different products since they have ordered three different products that order ID is getting repeated Clear. Clear everyone. This is why order ID is getting repeated. Meaning the number of rows is the number of product number of total order ID means total number of products ordered. That's why order ID is getting repeated. Now why…

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