Power BI With AI Full Course 2026 [FREE] | Power BI With AI Tutorial | Power BI Course | Simplilearn

What if you could take a simple Excel file, clean the messy data, build interactive dashboards, find trends, and even use AI to understand what the numbers are trying to say? This is exactly what PowerBI helps you do. Hey everyone and welcome to this PowerBI with AI full course by Simply Learn. Today, almost every business depends on data. Sales teams track revenue, marketing teams track campaigns, finance teams track profit, and operation teams track performance. But the real challenge is not just collecting data. The real challenge is understanding it clearly and using it to make better decisions. And this is where PowerBI comes in. It helps you connect data, clean it, analyze it, visualize it, and present it in a way that is simple, interactive, and useful for business teams. And now with AI features and tools like copilot and smart insights, PowerBI is becoming even more powerful for faster analysis and better reporting. In this course, we will start from the basics and slowly move towards advanced reporting, interactivity, data transformation, and AI powered analysis. First, we will begin with the basics of business intelligence and help understand how BI helps businesses study past data to make smarter decisions. Next, we'll get introduced into the PowerBI ecosystem, including PowerBI desktop, its interface, and how to start working inside the tool. Then, we will understand the two important ways of looking at data, which is measures, which are numerical values used for calculations and dimensions, which help us filter and group data. After that, we will create basic visuals like tables and matrix reports and then move into charts like column charts, bar charts, pie charts, and even donor charts. Next, we will learn how to improve reports using formatting and conditional formatting so that the dashboard not only shows data but also highlights what matters. Then we will explore the advanced visuals like ribbon charts, waterfall charts, scatter plots and combo charts to compare trends, rankings, relationships and performance. After that we will work with maps, slicers, filters and tree maps to make reports more interactive and easier to explore. Finally, we'll move into Power Query where we will learn how to clean and transform data by splitting columns, handling null values, unpivoting data, and preparing data sets for proper analysis. Then we will also look at how AI tools inside PowerBI can help generate insights and make reporting faster. So, this course is not just about creating charts. It's about learning how to turn raw business ideas into clear reports and useful dashboards with meaningful insights. Also, if you're interested in boosting your career in business analysis, do not forget to check out our AI powered business analyst course. So, this course is perfect for professionals looking to enhance their skills with the latest tools like PowerBI, Excel, SQL, all while gaining hands-on experience with real world projects. So, you will also learn how to leverage generative AI for smarter and faster decision- making. Our program is IIBAK V3 align and helps you prepare for certifications like CBAP and CCBA. You will also engage with 10 plus industry projects, 40 plus practical activities, and benefit from live online sessions led by experts. Plus, with Simply Learn's job assist, you will get the support that you need to land your next big role. So, before we get started, here's a quick quiz question. What is one of the main uses of PowerBI? Is it A to edit videos, B to clean, analyze, and visualize business data? Is it C to build mobile apps? Or is it D to write operating systems? Think about your answer and let us begin the course. So, let me introduce myself. My name is Mohammed Sadi. I'll be the trainer for this particular PowerBI sessions. Okay, which we'll be for next four weeks kind of a thing. Uh to say something uh about myself uh I'm into teaching almost from more than two decades. I started my teaching the year 2000 been handling with uh multiple been certified from the Microsoft as well as from the Oracle, MCP, OCP respectively. Uh been handling lot of programming languages like ASP.NET NET, C, MVC architectures and so on. Um handling like various databases uh like Oracle database administrations, SQL server, MySQL, posgree all the databases. Okay. And um so I do handle all the models of data analytics taking from the Excel to the BI tools like Tableau as well as the PowerBI and the databases all most of the popular databases like pos3S SQL MySQL you talk about Microsoft SQL server or the Oracle and also uh I do handle trainings on the Python for data analytics okay Python language as well as the Python for data analytics libraries and so on okay um and got a chance to handle uh trainings across the various segments, various clients. Um I can say hundreds of batches. I don't have a count of it. Yeah. So I enjoy my sessions and I always keep the session as uh interactive. That is what I generally prefer. Okay. Uh fine. Let's move ahead here. So with the PowerBI now uh just a small question here. So just before we go further here. So I just hope everybody have a knowledge on Excel uh like pword tables the lookup concepts way lookup x lookup uh working with the tables uh working with the modern functions of excel not entirely but but completely um okay not completely but worked on Excel. So I just generally say like you know Excel is u a place where you can play around data very freely. Okay. Uh because it has lot of tools here and the functions are very easy there. Okay. And the new enhanced functions you talk about the Excel 365 modern functions what you have you talk about a let you talk about stacking functions you talk about the new uh spillover functions or the dynamic array functions. They are really amazing. Okay. And um so there is a place where we can play around data very freely. Okay. And get more insights of the data. Right. Anyhow, so I don't have any knowledge on the BI tools as well but um no I'm not talking about BI tools. I'll be talking about the BI tools but um I'm talking about Excel kind of a okay fine. Hey um so let's move ahead here with um Microsoft PowerBI. Okay. Hey fine. So at the end of this session we'll try to understand what is BI business central okay understand the various BI offerings um we have different tools okay on the PowerBI desktop and finally we'll be working with the PowerBI desktop so we'll also identify the real world applications of PowerBI to address the challenges across the industries and the business functions okay uh where we can use the PowerBI and also we'll see like you know how do we install the PowerBI in today's session Okay. Um I think um if you have already installed that would have been better so we can move ahead directly kind of a things. Hey uh what is business intellisense? See generally when I talk about a business intellisense okay is a process of um studying the historical data getting the insights of the data and based on that insights taking uh creating a reports. Okay. A dashboard with the help of which we can take a smart business decisions. Yeah. This is a definition of sadic. Okay. U based on the experience like you know I don't like reading the slides again. So I always have um try to go practically kind of a things. Yeah slides are there but you know I'll I generally have seen this. So what did I say? A business intelligence is nothing but a process of studying your historical data, archival data we call it as getting the insight from that particular data and based on that particular data creating a reports with the help of which we can take a better business decisions a smart business decisions. Tell you what this is what is the definitions of any business intelligence and there are many BI tools. There are many business intelligence tool in the industry. So you do you know people know uh any name any such business intelligence tools like very popularly we have a taboo is one such very popular BI tool. PowerBI is one such click view is there. Okay. There are many BI tools. There is a SAPBI Oracle BI tools and so on. And out of all those particular tools, Apogia is one such tool which is trending in the industry in the market. Uh the reason can be it's not because very old. Tapio is there almost for more than two decades and um PowerBI is just around 7 8 years old and um when you see now Google trend if you look into PowerBI is more trending more in demand than any other BI tools even more than the Tableau. Okay. Uh Tableau comes in the second place. kind of a things I see. Okay. The reason is uh there are a lot of reason why uh one such is it's a product of Microsoft. It belongs under Microsoft. Second thing is um it has a um see like you know you need BI tools it helps you in extracting the data from the different data sources. Okay. Uh when I say a different data sources fine. Um so I just telling like you know so any BI tools helps you in extracting the data from the data sources. We have many data sources. We have many data sources like you know the data might be present in the CSV formats. The data might be present in the Excel files. The data might be present in your database servers like Oracle SQL server or anything or your data can be also present in the cloud. Okay. It can be present in any formats. Now this particular what happens is the BI tools should be capable enough to read the data from the different data sources and on that basis PowerBI is one such which supports the maximum number of data sources. So I can say it supports more than 100 different types of data sources. Okay. PowerBI supports more sources. That means we can read the data from many different data sources. clear this is one main reason why PowerBI is in the top trending even though it's a news BI tools compared to there are many other BI tools which is there almost from the decades old but still PowerBI is in the top that is one main reason the second reason is it has the data transformation tools data transformation is whenever you try to read the data so whenever you try to read the data you'll be lucky if you're getting a good data so you always get unclean in the data. So which needs lot of transformations might be uh formatting the it might come in the different date formats or you have to split the columns you have to split the cells um you have to do various kind of a things. So please certainly again okay uh it can be that uh it can be like um uh yeah so various uh this one so now power bi supports a tool with the help of which I can perform the data cleaning in your what do you call it as powerbi desktop itself so that means it has a tool called as power query that's a really amazing tool it's ETL tool we call it as so it helps you in extracting the data from the different data sources and performing the data transformation on that. Okay. And apart from all those particular things, it also has a data powerful data modeling tools. Data modeling is what uh when I go with this particular data sources, the data might be spread across multiple tables. I need to bring the data from multiple tables and create a relationship between that. Okay. So here you don't have to go for any other tools for data cleaning or data modeling. So PowerBI has inbuilt so-called tool called as the PowerB. If you have studied this power query and power pivot is also there in Excel also. Excel also has a power query. Excel also has a power pword. Excel also has a power muse. Okay. Uh power power uh kind of a thing tools which is mainly called as a data modeling which helps you to read the data from the different data sources and create the relationship between the tables. Fine. The next thing is uh it also supports the tools like uh what do you call it as u the data visualization part okay and when it comes to a data visualizations is nothing but the creating the charts. So here in the powerbi very easily I can create many different types of charts. So if you ask me how many 200 300 plus different types of charts yes we can easily can create it. So I can say it's very highly interactive charts can be created very easily. And other major thing is you know people who work on data analytics they come from Excel. Okay. And Excel is a product of Microsoft and PowerBI is also a product of Microsoft. So that the easy adoption is there. Okay. Uh a Microsoft product to another Microsoft product. The kind of a interface GUI the shortcut keys. Yeah you will have those kind of a relevancies. So those kind of a benefits you get it over here. Okay. And these are the major reasons where I can say that PowerBI is top friendly. Got it? Okay. Fine with this. Understood? The concept is clear. Hope I'm not rushing. Okay. Okay. Fine. Hey. Upart from that slides are there just to go through you'll be having this particular things. Now we will go ahead installing. See again when it comes to PowerBI uh softwares like we have a PowerBI desktop, we have PowerBI what they say on the mobile applications. We also have a PowerBI uh what do you say services which we can use it on the cloud. Okay. Uh we will be using the PowerBI desktop which we will be installing it locally on your machine and we'll be working. Um so let us see how exactly we install this PowerBI and how do we work on this. Uh have you people installed PowerBI? Hello. Yes. Not it. Okay. Hey uh if you have not installed it so what I will do is I'll just share the link where you can install this particular PowerBI okay uh so we can go get into practically um just go to any browser and search for the PowerBI desktop download. So search for this particular link PowerBI desktop download. So which is the Microsoft official site. Yeah. So we can just download from this particular link. Yes, in my case it is already downloaded. I don't want it. Okay. Uh you want I can share this link or you go to the browser just say Microsoft PowerBI desktop download and just hit on this particular download. Uh it supports only for the Windows operating system. So if you're using a Mac, you don't have a support of this. I hope everybody are using a Windows. This is the persona of uh um the batched u so what I'm taking so this is how the learners um so the review what you're given so it's something like you know actively work with powerbi is 2 out of 16 and the say I have some knowledge in powerbi okay so that means um we have around um 10% of the people who have been working okay so that is what it Okay, 85% of the people says no experience in PowerBI and when you look into the other profile kind of a things of relevant experience we have people from beginner limit is 93% uh advanced regularly working so we have experience with 7%. Uh preferred learning style. This is your batch care. This one persona preferred learning style. Okay. People prefer hands-on practice. Yes. Okay. So definitely I'll go with completely a practical subject. I'll go with the hands-on kind of a things. Um have used PowerBI as an end users where everything was integrated before. Okay. Fine. uh so you have a knowledge of using the power but you'll be learning how do we develop your own dashboard okay thanks and functional background uh we see that maximum people coming from the IT information technology so people have the program knowledge of programming am I right okay and we have 10% of the people from the freshers but otherwise marketing finance they deal with lot of numbers I believe is it so fine so this is going to be more of understanding the data, understanding the numbers, okay, working with the numbers kind of a things. Okay, data driven primary goal is helps in career growth, acquiring skills 41%. And getting certified is okay, just 5% wants to get certified. I shared one um Excel file. It's a sample supertore. I request you all to download this have it in one of the folder. We'll be using this as a data source to do the various analysis. I'll be sharing the many other files as we go further. So in this particular session I think we to start off with we'll go use this one in maximum of the examples we'll be using with this but for the power query and the data modeling I'll be sharing the other files. Yeah. So before we go further, so I have shared this particular file. We will use this particular file to understand the basics uh of PowerBI. So how do we work on the PowerBI? Okay. See now when you look at this particular file, it has three sheets. Uh one is the orders, people and returns. As of now, we will use only the orders. Okay? And in this order sheets when you see we have 21 columns 21 columns and approximately around 10,000 rows of data 9,995 rows of data with the heading it is 9,995. Okay. So almost 10,000 rows of data and 20 different observations are there. Okay. So now see as a data analyst or uh as a business intelligence your primary role is to explore the data. So to get the insights of the data get the understanding of the data so that okay based on that we can try to find out where things can be improved and based on that particular insights what you have got. So you're going to create a reports okay with the help of which we say hey this sales are this product has been selling good at this particular region but this same product is not been selling good in this region okay so where which product is selling best where that product has to be promoted so that we can improve our business okay so those kind of ideas we are need to create it right now for that purpose so when you look at this particular data so what is this data about. So what do you think this data is about? When you look at the headings, we can make out. No. So when you look at this particular things, it is dealing more with orders. Okay. And there is something called as see we have something called as row ID. Every row is uniquely identified and there is an order ID. So order ID is repeated because you know one order mean there can be many products. Okay. So the order ids are there and then we have order date when the order was been placed. We do also have what I call it as a ship date. When exactly the shipment has happened, what customer preferred, what mode of shipment. So we have a mode of shipment. When you look into this, we have a different mode of shipment like same day, first class, second class, a standard class of shipment. Apart from that, we do also have the customer details like each customer is identified using a customer ID. They have a name and they belong to some segment corporate segment, consumer segment or the home office segment. What kind of customer he or she is? So that we can do analysis okay how this business is having from the consumer segment. What is the profit I gain from the consumer segment compared to the corporate segment? Hey, what kind of a behavior of the customer corporate segment? So generally we see that corporate segments are like you know people who don't do much of bargainings. Okay. Or like you know might be they are the people who purchase in a bigger quantities. Okay might we can understand the behavior of that. We can try to understand like you know which segments of how much business we are getting. Okay. We can get that those information. So we have the information about the orders the shipment. Okay. We do also have the customer details what segment they belong to. We do also have some geographical datas. What country this particular order belongs to. city, state, region, postal code respectively. And also we have the product details here. So it says, hey, what is the product ID? Every product has an ID, the name, category, subcategory it belongs to. Okay. And we do also have some measurable values like sales, quantity, discount, profit. Okay. So what we understand from this one, this is something to do with the e-commerce. Okay. Uh e-commerce is what? U the online shopping. Uh this is Amazon credit. I can consider it as okay. So that means we have the details of orders, when it was been placed, how much time it took for the shipment, what was the customer preference, whether he wanted in the same day shipment or a standard mode of shipment. See when they go for a standard mode of shipment, there'll be no shipment charges. But they are asking for the first class or the same day shipment. So there'll be an additional shipping charges that they need to pay and all the things. So what is their kind of a customer's behavior? We are just trying to capture and also we are trying to find out like you know who is this a customer who is placing this order what segment he belongs to geographically we can try to find out how the business are happening as well as we can see the products based on the category and the subcategory wise and we do also have sales how much quantity was been placed whether it was been sold with a discount or without discount whether what is a kind of a profit when there is a heavy discount obviously there can be a negative profit okay so we have this particular data so this is about the e-commerce data uh you can get it from the chat but chach we have to tell explain the chach and then we have to tell him to generate the data set okay again the chach will give you some kind of random names or it'll try say customer A customer B customer c something like those kind of a things okay u so then again the way you are going to talk to a chat and generate it matters so any I've given you a directly a downloadable file you know please use those particular file and we'll go ahead and this a kind of a realtime data. Yes, sure. Okay. Fine. So, see why I'm taking this particular data set is it has a good amount of what I say dimensions. We can analyze the information geographically. I can analyze the information based on the customers segment based on the dates fields we have. We can even find the difference between the order date and the ship date. And we can find out how much time they have taken for the shipment. If the business is going bad, if the shipment is delayed, it can be the reason. I can do a lot of analysis. So we can do analysis what kind of a customer preference we can do analysis based on the categories subcategories of the products. We do also have like you know when there is a discount how many customer see there are some customers who come to the shopping only when there is a what do you say discount you know I have seen many people come go to Amazon only during this particular big billion days or so there is a big offer days no okay those kind of a thing they keep waiting for a Diwali offer uh republic day offer independence day offer and so on okay especially my like me I will always keep looking for those kind of a things so whenever I have to purchase something like you know always I say hey this Diwali offer or this independence day offer I just look for that kind of a things I don't know what kind of a products I get it but I always keep looking for that okay uh things okay it happens like you know so I just want to know hey whether the customer prefers coming during this particular offer times when there is a discounts or no discounts may also there are customers who are purchasing so we have all those particular things so I can say so I'm just like this particular data set because this I can analyze the data based on the different dimensions okay fine I think we will move ahead here. Let me Okay. So now so what I will do here is okay. So first thing is whenever you look at the data. So whenever you look at the data so our job is to get the insights of this. Okay. So whenever you look at the data so I always keep telling as a data analyst you need to have a good skills on uh getting the insights of the data and to get the insights of the data you should have the skills of torturing the data. Okay. Asking questions on the data. See uh when you look at this we have a different categories of product. We have a different categories of product. Okay. So what are the different categories of products we have? U so that is a question. So first the next question I say hey hey we have furniturees, we have technologies and we have office supplies. Okay. And then uh the immediate question comes is um what is the total sales for furniture? What is the total sales for technology? What is the total sales for office supplies? Is it he we say what are the different categories and each category wise what is the total sales subcategory wise to what is the total sales under furnitureures we have a bookcases chairs tables and so on. So each category wise each product wise how the business is happening each region wise how the business is happening country wise city wise state wise uh segment wise customer wise or we have the order date here okay year wise each year how much business is happening quarterly wise monthly wise daily wise how much business happening. So we try to ask this kind of a questions is it okay fine. So now based on that so what we say is whenever you look at the data we always see the data from the two perspectives. One is the data on which you can apply the calculation. One is the data on which you can apply the calc uh calculations. Okay. So like example when you see sales quantity discount profit these are numerical values when you look at the data this particular values. So we say hey what is the total sales what is the total profit what is the average sales what is the highest sales what is the highest sales in any region what is the highest sales for any particular category or product okay uh what is the kind of a profit percentage so that means when you look at this particular data we always try to apply the aggregations on that means the calculations on that so based on that we call this fields as measures we can call this fields so or as measures these I call it as measures. Apart from that we have this particular non sorry uh non-measurable values. Okay. Or we say it's a categorical datas like category, subcategory, region, segment, order date or we say um uh country, state. So these are data on which you cannot apply the calculations but yeah we can group it. Hey category wise what is the total sales? How many different categories are there? Each categories may how many sales have happened? each region may how much sales have happened each um say segment may how much sales have happened how much profit has happened we try to do that so these non-numerical datas or the discrete values we call it as a dimensions okay dimensions are the discrete values whereas the measures are the continuous values got it hello okay this is the first thing uh this is very important thing I can say Okay, whenever you look at the data, we always see the data on which you can apply the calculations and the data on which you can just do the groupings. Okay, so the data on which you apply the groupings we call as the dimensions or we call that as a discrete they are the discrete values and the data on which you can apply the calculations they are called as measures. They are the continuous values. Okay. So I cannot find out like you know hey what is the total sales of 261? No, every has their own values isn't it? So I can always say like you know hey I want to see those products where the sales value is more than $100. Okay. So those it is a kind of a continuous but here mainly we try to do a aggregations like what is the total sales, average sales, minimum sales, what is the highest sales. Okay. So those kind of a things but here we cannot apply those calculations. Only thing is we can have a count hey how many different categories are there? How many different subcategories are there? Got it? Okay. This is the first thing to understand. So thanks. Hey now uh since like you know before I get into the PowerBI so I always say like you know in Excel if few people have worked with the pivot tables I hope everybody have worked on it is it uh isn't that amazing tool for summarizing the data analyzing the data again uh very uh amazing tools tick tick tick and the job is done so that is just few clicks and we can analyze this complex data very easily so almost 10,000 rows of datas are there so I just want to know each region wise how sales how much sales have or what is the total sales or category wise sales I can easily do it. So what I do I generally go to this particular pivot table and say hey I just try to keep it here itself is it all know about p tables no um so if I have to know what is the total sales I just click on the sales see as soon as I click on the sales you know uh sales is the numerical value it is automatically taken to the values and it has applied the aggregation as sum of sales okay and you can see we are getting the sum of sales here this is the total sales 2.3 million okay 22 lakhs 97,000 so which is 2.3 million Now the same sales I just want to find out for each region wise okay or you want it for region wise right so where is the region here so I just click on this as soon as I add a region you can see here the region doesn't have a numerical datas it is a character datas so automatically the region is being put uh picked into the rows and it is taking a distinct value you can see hey out of the 10,000 rows of data hey this were the four regions were there okay and each the same 23 lakhs okay is been divided did something like this in the central region what is um five lakhs okay uh things so out of 23 lakhs you can see five lakhs of business happened in the central and the say 6 7 lakhs business happened in the east region south region is 3.9 lakhs and say west region has done 7 lakhs 25,000 okay fine um this is what it has been automatically able to do it so this is the kind of analysis what you're trying to do is it so okay I want to see the category wise how the sales are happening within that subcategory wise Okay. So it's an amazing tool like you know with AP tables. Now we'll try to do something similar to this in PowerBI. Okay. So fine. So now yeah that was just to get uh no understanding about this particular data and things. Now what we will do is we'll try to do a similar kind of a job with the PowerBI. Okay. So first thing is we need to extract this data. See PowerBI doesn't store the data. Excel beauty is what is it? Excel is a multi-purpose purpose kind of thing. Excel can store a large amount. You can store the data. Okay. Uh you can even perform the data transformation. If you have worked with the power queries in Excel, there is even the power pwords in Excel. Yes, we can perform the data modeling in Excel. There is also the power views in Excel. Okay. It has multiple things and it also has lot of features in Excel. Okay. Things okay but in the PowerBI desktop okay or PowerBI they don't store the data. So when it is needed we can pull the data from the different data sources and with then we go ahead creating the various uh visualizations u data transformation all the operations we can do it okay what I said so it has a power query it has a power data modeling and various things so now we will go with some basic u uh the summarization of the data okay so what I will do is okay um I'm just closing this don't do any changes on this okay just say don't save this I'm just closing Now I just want to read this particular uh file into my what is say PowerBI. So what I do I just start my PowerBI. So I'll just go to the PowerBI desktop. I just go to the PowerBI desktop. So I'm just going to this particular PowerBI desktop. Now we can read the data from the different data sources like say example this is one lake Excel workbook SQL server and so on. Okay. Now as I said we can read the data from more than 100 different types of data sources. What did I say? We can read the data from more than 100 different types of data sources. Now uh where is that? So we can see here most commonly we use Excel because people as I said jump from Excel to this but in the real time Excel is not preferred for storing the data for and this one analytics. The reason is Excel occupies a lot of space. Okay. And the same data you save it in the CSV format, it occupies very very less space. Okay. Binary format, CSV formats. Okay. Or when the data is very large, the data will be stored in the database servers. They have more security, multi-users and all those things. So now if I have to get the data from any data sources. So we can see we have this option here called as get data from the other sources. Okay. Most commonly we use Excel. So we can directly hit on this and go one and go. But as of now I'll show you there because I told that 100 numbers. No. So I have to prove that I'm right. Okay. As soon as you say this get data from the other sources. You can see it shows me the list of data sources here. And if you count I'll not be wrong there. Okay. So I will be reading the data from the Excel workbook. You can just select it. See we have lot of it can read the data from the different types of database servers. uh Microsoft fabrics, power platforms, Azour, online services, okay, the file systems and so on. Okay, so I'll just go to this particular Excel workbook because my data is present on the Excel and I have to read the data from the Excel. After selecting, okay, the type of data source that you wanted, we will just click on the connect. Okay, I'll just click on this connect. When I click on this what you say connect it just says hey where is your data source present we can grow browse and go to the location where your data set is present okay so I have shared the file to you you have downloaded don't keep it in the download just have a separate folder might be with my name or something okay and have the data set and try to read from that particular location okay so uh I'll just say I'm just using this particular data set sample supertore which is present in this application fine so I'll just select this and just say open select the data source file here and click on open now we are telling that okay I'm reading an excel data and where since excel is a file system I have to see the location where it is yes I gave the location I said uh loaded it is getting loaded now you can see here I showed that we had three sheets there orders people returns it is showing all the three sheets apart from that in excel we have the concept of dynamic tables there have created the tables you know based on that it is referring to the orders those are the tables okay uh need not be like you can you just read the data from the sheets itself okay so when uh since I said I want to read the data from this particular file called as sorry sheet called as orders in that particular file so it is showing the preview of the data yes yeah this is what the data I showed this is the data I wanted to load it just to cross check have you selected the uh data set. Okay. And then we click on the load. Then again click on the load. We'll be performing doing this data transformation and all this thing the power query in the coming sessions. Okay. So we'll go to the load l a d load. I'll just click on load. When you click on load, what happen? The data gets loaded to the PowerBI desktop. or doing parallelly with me. Okay, if not you can do this the data gets loaded. Okay. So you can see once the data is loaded on your right hand side we have this particular data pane. So which just shows that there is a table loaded called as orders and when you just expand this it shows me all the fields whatever the fields I showed you there. So all the fields are been kept here. Oh here it is sorted in alphabetical order. So it is category city and so on. All the fields what is there is there? Yeah. Okay fine. Hey, once you've done this one um so now what you do is um uh as soon as you click on the sales you can see automatically it creates a card for me telling that you know the total sales is 2.3 million it's so easy is it okay so there in Excel we use a pivot tables and then I have to go for sales and you get a number which says 22 lakhs 97, uh 287.973 which is almost 23 lakhs. So but here you can see it is summing up all those particular sales value and the way it is being presented is in the best readable format 2.3 million. Yes. Okay. Uh all are able to do this much. If you observe your interface also is slightly different. You don't have this as a build suggestion but you have two different tabs here. Is it okay? And I think you're missing out with this things also. there are some things missing is it okay the reason and I do also have lot of many other um uh tools and all this particular stuff is it cool now the reason is um see what happens is powerbi gets updated very frequently okay see generally when you talk about any softares to update the new software they take at least 2 to 3 years minimum 2 to 3 years okay because first the master software is released in the market Okay. And then they take the reviews. Okay. And they feedbacks for one year and then next one year they work on that and they take another 6 months to one year to release that market into the market promotion all those things. Fine. So it takes 2 to 3 years for the new software to come. But here by way is not like that. They are coming out with updates on every 30 days. Every month on month they're coming with updates. Now you want to get updates for that. You know if you have to uninstall, download the new software, reinstall that becomes a tedious work. Is it? Okay. So to get the features, the preview features, okay, the new features, updated features or the preview features. So we can do something like this. Just click on the file. Just click on the file. Under the file, you can see there is an options and settings. In the very bottom, we have this options and settings. Under the file uh when you click on the file you have this options and settings just click on that. Under the options and settings again we have the options. Under the options and settings again we have the options. Just click on that. under the file options and settings and then options. When you click there, so you get this options. There you have something called the preview features. You can see this preview features. Okay. In the preview features, so in my case uh you can see all the checkboxes are selected. In your case, maybe most of the checkbox is unselected. Am I right? Am I right here? So you can check all the check boxes. You can select all the check boxes. After selecting you have the okay button in the bottom. You just need to click on okay. So click on okay. When you click on okay it'll ask you to restart it is you don't have to restart your machine. It is just the PowerBI. You need to close and open the PowerBI. That's it. automatically you'll get the updates and you can see your interface will be same like in my interface. Yeah, restarting PowerBI is just close the PowerBI and open the PowerBI again. That's it. Restart PowerBI in the sense is just need to close the PowerBI and open. You don't have to restart your machine. Okay, fine. So once you open it, you'll be able to see your interface is same like mine and now you click on the sales you should get a card. Now when you select this particular sales you should be able to get a card like this 2.3 million. It's like a scorecard which gives you a complete summarized value. When you are watching the match cricket or any kind of a match you know uh it shows you a summarized value. So our mere focus is on that card. No keta. So what is the total score? Okay. How many wickets? What is the run rate? Current run rate. So those summarized values we try to show it as a cards. Okay. Then the cards comes with a bigger font. Yes. Okay. So directly the sum. Okay. Fine. We'll look into what is card. Okay. But now uh we will go with um what you call it as a tables. Okay. Now another thing is okay. uh before that you know uh you try to select uh just click outside of this don't select the card okay now you click the regions click the region what is happening you are getting a table with the unique regions so we are able to do this so what we understand from this one is when you select a measurable values it is performing the aggregation the total sales but when you select a discrete value, okay, it just gives me a discrete uh what do you say a distinct um um dimension that you have selected. Okay, so you have selected region it says oh you have four different regions there and have it something like this. Okay, now to get things going. Okay, so this is something to do with the data. Okay, this kind of a symbol. No, database symbols we see. Okay, so it shows me all the tables and the fields. And when I talk about this one, this is for building your visuals. Visuals is you want to create the different types of charts, tables, summary. And you talk about this symbol here. This is formatting. This is used for formatting. Okay. Uh if it is hidden, just hit on this data build format. Okay. I think so you'll be working on this particular canvas for creating the report. Okay. So now what happens you know if you keep all this open so you'll be compromising your canvas space. Okay. So based on your requirement keep only what is required you can keep it open or it just pops out automatically. You can see in and out is very flexible here. Pin outs and in and things and so on. So we can pop out and pop in things so that we have a better uh space for us to work. Okay. So I don't recommend you to always keep it open but yeah it is on the fly in just a single click it just collapse and expands respectively. Got it? Now okay uh I'm just deleting all those particular cards and everything. So now we will see with the tables okay so when you see in this particular build we have the different types of visuals okay which we can create uh the different charts are there and so on. You can either take it from the build or even from the insert uh option menu. We have the same thing as well as in the home also we have the same thing either from anywhere you can use it. The first thing is we will take this particular table. Okay, what is a table? Table is nothing but is a collection of columns. Okay, we'll try to work with the tables. Now, so I'll just select this particular table. As soon as I select this table, we can see a small what you say the interface has been created here. It says you're going to add the table. Okay, you're going to add the table. Now, table is what? What? Table is a collection of column. Please mute. No, what is that? So, uh it is a collection of columns. It is just a collection of columns. So, as soon as you add this, you can see in this particular builder, it says to add the columns. what columns you want. You can add anything. You can add a dimensions. You can add a measurable values. You can even add the date fields. Now what I will do is again see if I just say category. Okay. Um when I say category, you can see it shows me what are the categories are there. So we have furniture, office supplies and technologies. Fine. Apart from that, okay, when you scroll here, you can see we have more ad items. You want to add each category. What is the total sales? I just hit on this add. And you want to add the sales. We can search like this and we can do it or you can even uh type here and we can get it say sales. So it shows me each category wise what is the total sales. Okay. Or if you go to the build options here we have more better interface here. So it says what fields is needed. So like say example you want to add the region. Select the region and I say sales. It shows me each region wise for the sales of app. Got it? And now see what happens is here see in Excel we call it as sheet. Okay. But again in a single sheet we can have multiple tables, multiple charts and everything. But in PowerBI we don't call it as a sheet. We call it as page. Okay. We have the option of adding the new pages here. Okay. Now when I say page, page is like a report. We can have multiple visuals. It can be a charts. It can be a tables. It can be the cards. Okay. Also, we have a slices and all these things. Okay. So, we'll be learning all those things. Now, when you look at this one, it shows very small interface here. Okay. Now, you want to enhance that we can go and format that the font and all these things. But at the same time, we have something called as a focus mode. So, when you see when you select this visual, we have this one. This is called as what? Focus mode. So focus mode is what is hey I just I'm working with this particular visual I want to bring the whole this particular visual to the whole screen so that I can look at it more clean okay more closely so we can just hit on this focus mode it just brings in front of you and you get more better visibilities and when you say back to report it comes back to the report because in a report you can have multiple visuals and if you're working on a particular visuals you want to look at the individual like label and all those things I can bring into the focus mode. Okay. Right. And we say back to the report it just comes back. Focus mode is it is showing only one single um what do you say the visual okay only one single object is covering the whole screen. Okay. So that we can work on that and once it has been done say back to report. It is a report. Report will have multiple visuals like this. Visuals is representing tables or charts a slicer or any objects. So now see you want to do a cosmetic on this your makeup job I know this very uh small not readable uh and when I see the table I want the heading with a different color the for total I want in the different colors you want to do those particular kind of a things so what you do is just take this paintbrush okay you have a brush here also okay you can go to the more options or from the right hand side also you can see that is the formatter paint okay so we hit on this one to do the makeup job here I can just go here and see these are called as the values you know the totals values and so on just click on this values and you can see it shows what is the font you want what is the size of the font bold italics color everything can be done so I want I don't by default it is given as a 10 points okay see UI so you can change the font okay so I don't know which is a good one whatever the default is there I'll go with that but I'll say I want to have a bigger font I'll increase the font size yes okay so black and black and colors like colors you want to change for the text you can just do that alternate text also can be done. Okay. So those kind of options are there. So you want to have a totals with a different color. So we can go even to the totals or you want your totals to be displayed. So you want the totals to be displayed in a different color uh with a different background. Yes, we can do that. I'm very bad in color selections but yeah and we have a headers so all names are like English names you know column headers how you want your headers uh headers may I just want to have a text color yeah and I just want this to be as 20 bigger it's too big is that 16 something on a So you want to have a different color. We generally try to keep it as simple as possible. That's it. Nope. Professional looks kind of a things. Default is this. Yeah. So we can give something. Yeah. It is in. And you want to increase the font. Yeah. So that you can go to the values and just work on the forms to have a better concept. It's okay. Now we just got the subcategories and the sales. Okay. When I took the sales automatically it has taken the total sales. Okay. It has been grouping the totaling sales for each subcategory. Right? This is the total sales for each region. Now the default aggregation is sum. So which generally happens in the p table also. Now when you take a dimension it takes a unique values. when you take a measurable value uh it takes the sum okay as a default aggregation but I say no I want to have an average sales I want to know okay things for each region what is the average sales you want to go for that so I can just select the respective visual okay and we have the sales no next to the sales we have a small arrow there just click on that instead of sum just change it to average this shows me the average sales or you want to change it to higher sales in that region over sales in the region. We can just do all those things. Okay. The default is sum and most commonly we use sum. Okay. This is how we can change the different aggregations. Okay. Hey, that is there. Now the next thing is you want to add multiple measures. Say say example we take a region or subcategory. I think I'll take a subcategory. Okay. Uh now we have a sales with the sales I want to have even the profit. Okay. So I can just add the profit here. Okay. Um so when I just hit on this say profit it just shows me the profit. So that means it tells me each subcategory wise what is the total sales and what is the total profit. So we can see here I just added for each subcategory total sales as well as the total profit. So it says accessories we have a total sales of 167k and the profit is 42k. Okay. Appliances 107K is the sales and 18K is the profit. Arts 27K is the sales, 6.5K is the profit. Uh you can add multiple dimensions and multiple measures. How much quantity has been sold? Yes. So we can see accessories. Oh, we have a total sales of 167K for which we have 42K is the profit. How much quantity is sold? 2,976. There is almost 3,000 quantity is been sold. Okay, we are able to add multiple dimensions and multiple measures we can add. I can just have a slicer say which talks about the category and um I can just say furniture. It shows me one is the furniture, office, supplies, technology but I'll come to the filter later. So not we'll not confuse with this. Now how do we do that one is again just get into the format. All these are formatting features guys. Okay. Uh now just select this particular visual. So you are applying the formatting on this and there is something called as a specific column because see when it comes to column headers, totals, values, grid, style and all these things are a general format that means you are formatting at the whole table level. But here I want to format based on the individual column. Okay, a specific columns. Okay, so you can see we have this option here called as a specific columns. Yeah, you can expand this. Under the specific columns you say what is that column you want to format. So I want to format the sales. When you select the sales so we have a text color back color and all the things but you want to change the display unit. There is a display units here. Just select this and say what is that? You want in thousands. Yes. 330K. You want a decimal places. No I don't want the decimal places. Say zero. Cool. Got it. So whatever the display formats you want you can just format it. Hey this was something about the table. Now somebody asked me about the questions on percentage. How do we get a percentage? Say example. So I'll just take this particular table here. We have a region and we have a sales here. Uh central region have a sales of 500k. East has sales of 678k respectively. Okay. Uh I don't want to see the numbers like this but instead of this I want to see this in the form of percentage. How much percentage of the sales is contributed from the each region central how much percentage of the sales that is being contributed east how much percentage of the sales is contributed I want to look for that one so in this case what is that we do is just select the same thing again okay go to this particular build in the build okay we have this option uh sum of sales you know just right click on this right click on this okay and here we have something called as show values as where we have a percentage of the Grand you can see here it shows in the form of so from the east region we have 30% of the business coming from the east region 22% of the business coming from the central region 31.6% business coming from the west region and south region we have a very low business only 17%. So highest business coming from the west is 31.6% and the lowest business coming from the south region which is just 17%. Okay, I think this was another question what I saw in the chat. Hey, I don't have a habit of looking into the chat but I think when I during the break time I just went through this was the question. I hope I have answered all the questions. See just select the table. In the build we have a sum of sales. Under the build we have a sum of sales. Just right click on that. We have this option here called as show values as. Show values as. And there we can see we have this option here called as percentage of grand total. Percentage of grand total. Click on that. Yeah. Fine. We'll move to the next one here. Now we have this particular table. It shows me each subcategory wise how the sales have happened. Now just imagine I want to add one more dimension to this. The phones. I just want to know the phones. How much they have been sold in the east region, the west region, central region. Um yeah I want to see the each region wise how much they have contributed. So what I do is I just add a region to this. I just select the region. I just add one more dimension region. So as soon as I add the region you can see here. So what is happening? It just says like you know the phones. Okay each product each product when you see here so that is being sold in each region. So that means it says accessories whatever the total sales was 1 lakh 67,000. No 167k. You can see it is divided into region. Okay. So that means like you know it says the accessories the total sales of accessories in the central region, south region, east region, west region. Then again it says hey appliances in the each region wise how the sales have happened arts how the sales have happened in the each region. It is showing this. Okay. Now in this case what happens? It becomes difficult to analyze this data which is running like a long this one. Is it the second thing is I don't know what is the total sales in the central region. I don't have that. I don't know what is the total sales of accessories. No, it has been further drilled you know under the each c subcategory each product says here region wise how the sales has been done. Okay. So instead of seeing the data like this it'll be better if I can put this in data in two dimensions is it rows and columns that is what we generally do on the pword tables. Okay. Now in the tables we don't have that rows and columns we just have only the columns. Now for that what we do is we do also have an uh another thing called as a matrix. We'll go to the matrix now. Okay. What is a matrix? Matrix is nothing but a two-dimensional data. Okay. Where is the matrix? Next to the table you can see there is a matrix here. Next to the table you can see that there is a matrix here. We can see there is a matrix. Yes, there's a matrix. This was a table. This is a matrix. So where you can see we have the row headings, column headings and the data. I'll just select the matrix. Okay. Now I'm selecting the matrix here. Now when you go to the matrix since you have selected the matrix here. So we can see that we have three things here. Okay. What data you want in the rows? What data you want in the columns and what data you want as the values. Okay. Now I say in the rows I just want to have a subcategory. And in the values I'll say measurable value I'll say sales. So we are able to see the subcategory wise how the sales are happening. So you want to copy the same formatting features. We have this format painter and paint it on this. Yeah it takes the formatting features also. Fine. So here you can see uh each product. Okay. What is the total sales accessories? Same like a table but in the case of um what do you say a table when you add a region. So this was further divided with the regions and it was splitting the number of rows. But for that purpose what I do is when I go to this matrix we have rows and columns. I'll go to the columns and there I'll add the region when I add a region here. So we can see we are able to get okay the informations like okay so how the sales have happened in the each subcategory okay accessories the total sales is 167k okay chairs total sales is 328k we are able to see each product what is the total sales as well as we are able to see what is the total sales for the region central region what is the total sales east region south region west region we are able to see the region wise total as well as we are able to see the grand goal. Find all apart from that we can also see okay this is nothing but a particular product in a particular region how much sales of so that means we are able to see the accessories have done a sales of 167k but out of that 167k we see that in the central region it has done 34k in the east region it has done 45k in the south region it has done 27k and the west region it has done 61k K. Got it? So that means accessories is more sold in the west region 61K. Then is the east region 45K. There's a big difference. Then we have 34K in the central and the very low sales coming from the south region. Got it? So we are a not only able to see the information more easily. Okay. Since the data is in the two dimension, we are also able to get multiple aggregations. Here we are able to see the category wise total, the region wise total as well as the category wise total for the individual region and also the grand total. Got it? So this is your matrix where I can present the data in two dimensions. Apart from that we have all those features of formatting specific columns and all the things. Yes, we do all have all those things. I don't want to spend more time on the cosmetic work. So makeups and all the things. All good were you? Hey, apart from this one more thing what I like in the matrix is we can have a drill down information like say example I'll just take the same the matrix okay now I'll take hierarchical data okay like say example I take the category and I also take the subcategory that means under each category there are some subcategories okay and I'll take the values as a measurable value you can take either sales profit or anything I'll just take the sales as a measurable value now when Look into this. I've just taken two things here. Okay, subcategory and category and subcategory. Then the values I've taken as sales, sum of sales. Now when you go with this one, so what you see here is okay whatever it is. Hey, now you see that uh it is showing me the each category wise what is the total sales happened. We see that furniture we have a sales of 742K, office supplies 720K, technology 836k respectively. Okay. Now uh there is a plus sign here because under category we have a subcategory added there. So that means when you hit on this plus sign it expands. So under technology we have accessories, copers, machines coming under that. Under furnitureures we have this chairs, bookcases and things. Instead of expanding the individual we can also go to the drill with the hierarchies here. Okay. So we have two things here. Go to the next level. What is the next level there? It's a subcategory. It is showing me the subcategory or category. What do you want? You can toggle it. Okay. I say no, no, no, hold on. I want to see the category and within the category, I want to see the subcategory. I want to see the category and I want to see the within the category I want to see the subcategory. That means I want to see this information with the hierarchy. So we can drill with the hierarchy. Here we have this option here called as drill with the hierarchy. So the second option here drill go to the next level of the hierarchy that means drill with the hierarchy. So that means it shows me with the main level as well as suble under furniture this subcategories. So we are able to see what is the total sales of furniture. Under furnitureures we have this four different subcategories and what is their total sales. Office supplies the total sales and under office supplies we have this other subcategories. Technology we have a total sales of 836. Under technology subcategories here and their individual sales. Got it? We can easily do this particular drill. This is something which I really like it. Uh when I just drill with the hierarchies here, it is just going Hey, now we'll go with the hierarchies here. See, we have two things. One is the next level. Next level will show me the quarterly wise, month- wise, what is the sales? Okay. Or day wise, individual day wise how the sales have happened. This is a cumulated value. So that means when I say this is the Q1 sale, Q2 sales, we have four years data. It is the accumulate in every year there is a Q1. It is summing up all the Q1s of all the years and saying telling this is the total sales. Okay. So when I go to the month wise says January the total sales of January irrespective of the year but I say no I want to show as the running total. Okay. So you drill with the hierarchies. When you drill with the hierarchy it says and each year the quarterly wise and each quarter you want to see the month wise we are able to see. Okay. So that means here what happens is when I drill with the next level it shows me the accumulated value. Okay. Accumulated value means what? Hey, this is the January sales mean irrespective of the year. Okay. And I want to drill with the hierarchy is like you know that is drilling 2018 within that year quarterly wise within that year within that quarter month. What do you say month wise okay so now we can interchange this one. So what I wanted is imagine like I don't want the quarter you can just remove the quarter each year within the year month wise or I want the year in this particular column. So I can just take the year and place it here. Now is it I can remove the year from here keep only the month and in the columns go to the order date and just select only the year. So this shows me in the matrix where I'm able to see the year- wise total month- wise total as well as within each year month wise how the contribution is happening. Now the next thing is hey just before I go with the visualizations like you know um conditional formattings you have worked in Excel. Now I always say like you know we use the conditional formatting for a better understanding of the data. Okay. So I say uh we use the conditional formatting for the better understanding of the data. We can understand the data better with the help of the conditional formattings. Okay. So in what sense is see we have the accessories which is sold 1 lakh 67,000. Is it a good sales? If you have to know that I have to compare that with the each and every value when I compare with accessories. Yeah. 1 lakh7,000 and 1 lakh 67,000 it's way ahead you know 30 40% higher sales okay and when you see the compared to arts oh this is very very good but when it come to binder no no no no no again books is very higher so there are many products which is higher than this and there are many products many many products which is lower than this so based on that you know becomes difficult to judge whether it's a good value or bad value or an average value or above average or below average so it becomes easy when I use the conditional formattings what we'll do is uh I'll just select this sum of sales. Okay. And I'll just go to the condition formattings. I like to go with the bars here. Okay. And by default it shows a positive bar blue color. I'll go with the default one. I'll just say okay. So you can see here it has been filled with those particular bars here. So by seeing that you can come to know that hey accessories is just above 50%. Okay. It is just above average or average or just above average. Okay. And we see that chairs and phones have have done the highest sales. Okay, overall chairs and phones they have done the highest sales. And we see that hey there are lot of outlier. So we see fasteners 3,000 we can see very invisible and compared to 3 lakh 30,000 this is very very small. No not even 0.001% of the phones is it? So we have too much of outllayed values but that is what we are able to understand here. So we have some products with the small value products. Okay, the name only says labels, envelopes, papers, their value itself is very small. So that means the sales is very low and we see phones we cannot compare as it. It's a big value kind of a things chairs for you and all they have a high value sales fine. Yeah. So we are able to understand in that way um like you know what are the products are above average which all the top leading products okay so which are the products okay which is doing a very very low sales we are able to understand the numbers. So that means without even reading the numbers I can easily come to know okay where we have done a high sales where we have done average sales or what is the value of this paper it is below average low sales kind of a things that is what we are able to understand okay so I can say that we can understand the data better okay fine we'll move ahead here now the next thing is I want to apply the conditional formatting for the profit where I'm getting a negative profit where I'm getting a positive profit so I can do the same thing I say take the sum of profit here and I can just apply the conditional formattings and I say I'll take the same data bars but profit can also be a negative value no the profit can be a negative value so if it is a negative value I say I want a red color bar positive value let it be blue or if you want a green I'll go if you want a green color you can change the color like say example say okay hey today was just an start kind of a things um uh where we just understood what exactly is one of the very powerful business intelligence tool. When I talk about any business intelligence tools or nothing but a tools which works on a studies or historical data gets the insights on that and based on that particular insights we are going to create a reports with the help of which we can take a better business decisions. Now when I say it performs this so the first thing is the PowerBI has many components. So one is we have a power query the direct cleaning components. We have a power pivot data modeling. We have power views where we can create the visuals and we have a powerbi services where we can publish the report okay to the cloud. From there we can share it. So we haven't gone for all those particular things. We have to learn all those particular things. Today was just an start of knowing like you know okay what is data? How do we read the data? How do we apply some kind of a calculations on those particular data and then the tables and matrix which is very similar to the pivoting concepts? What do you use it in Excel? The same kind of a things. So I can say the pivot table is an amazing tool in Excel for doing the summarization of the data, analyzing of the data and so on. So something similar to that we have done in the PowerBI. Okay, hope it's interesting. So tomorrow we can go with some kind of a charts creating the different types of charts. we can do the some visualization part and then we can go to the power query so where we can perform like we'll see how do we take some raw data and clean data and how we can do the cleanings yeah hey now you know heat map analysis like you know I can apply a conditional formatting on this one also okay so now you're see always numbers are I always keep telling this you know numbers are only good when it comes to your account is that the bigger the number is more happier We are yeah but uh if you have to get some insights from your numbers okay small numbers are good there big numbers are very difficult and when you have more numbers you know it becomes really very um scary kind of a things now I say no from this I want to get the insights like say I've just taken this year and the month wise sales okay now I just want to understand during which period of time the sales are good during which period of time it's more challenging so I want to understand that So you can just apply the conditional formatting for this. This is sales, you know, sum of sales. I can just say, hey, sum of sales, I just go to the conditional formatting. I'll just give a background color. Okay, I'll just go with the default one. And you can see the way the colors are being applied, it just tells you, hey, the sales are more good during the end of the year. So we see that September, November, December the sales are very good. Okay, the highest sales have happened in the November 2021 and the lowest sales have happened in what is say um February 2018. Okay. And we see that January, February being a very challenging the light. So the kind of color the way it has been colored here the intensity of the color shows you. Okay. Uh high what is it say? Dark color is high sales and light color is low sales value. So we see that okay the sales are very challenging during the end of the year November, December and September. And we see the January, February is something like you know we have a very low sales. February uh sorry March there is certain something good but um April to August are kind of average sales but the sales are good towards the end of the year that is September, November and December. Okay. So yes we can just do those particular. So if you want you can have more colors kind of a thing. So in the background colors you want to say okay maximum value with the different colors you may say high value with the green color the low value with the red color you want to do those things I can just say hey low value with the red color mid colors you want to have uh something like a lighter color and I want to say what is the mid-range or something say no so we can easily come to know all the things this is similar kind of a formattings what we apply in excel no in excel also is always same thing we do it okay so we are able to do I think this is called as generally eight pepper heat map analysis. So high values okay we have the high sales towards the end of the year very low sales very challenging during the start of the year January February March spring season no so I think it's a very uh it clearly says that you know uh sales are based on the vacations and holidays so we have September November December kind of a things a lot of vacations holidays and there's a retail business you know we have a black Friday okay which promotes for the retail business okay and that is uh boosting up the sales during the end of the year and start of the here I feel people are busy with the projects or something people who are from the US they should tell me if correct me if I'm wrong here okay um they are less in spending in the retail segment and they are more busy with their official work looking for a new projects and things yeah okay so that is what we are able to understand and see based on this we can look at like you know how promotional activities you do so January February is very challenging for the retail business doing a lot of promotional activities there having lot of stock there becomes a dead investment. Okay, we know that every any every year we see September onwards there a big sale coming. So we can have a better planning month or two months before itself like what kind of a promotional activities we do, how much stock is required, okay, what is the kind of a manpower or resources required for that. So have a better plan and have a better execution and so that we can have a better um what do you say business kind of things can be done. We can have a better planning by looking at this kind of historical datas. Okay. So with the help of the colors you know the same data the same numbers it becomes more easy to understand and we can take a better decisions on that. Yes. Okay. Now we all have to look at the data from the business point of view. Okay. Hey this was just like you know the very intro. So we haven't seen any kind of a charts. So next session we'll start off with the charts. Okay. Maybe the next two sessions we can see with the charts and then we can go with the power query. Maybe two to three sessions we can look into the charts itself. We can we have lot of things to do with the charts and then we can go to the power query. So one or two sessions we can discuss about the power query is very important tool for the data transformation data cleaning jobs. We can see two sessions we can talk on the power query itself and then we can go to the data modeling and DAX calculations and then we'll see about how to use AI in PowerBI. Okay. Are there some kind of AIdriven visuals are there? We'll look into those um kind of a things and how we'll also see how we can generate this kind of a DAX calculations with the help of AI tools or even with the chat GPT how we can generate this. Yes, I incorporate a chipity in everything. Now even in Excel, I do use a lot of chipities to write the Excel formulas and all the things. So it's not like I don't like Excel. I really like Excel. I love Excel a lot. But with the help of a chat, we can do really amazing things. It speeds up the job like anything. See um if you have to read the data from the excel. So the first thing is to start off with powerbi. Okay. Uh we just click on the start. We say power p o w e r power bi. Okay. There's a software. We need to open it something like this. Okay. And here if I have to read the data from the Excel, I've already shared the Excel file. Is it yesterday? I'm using the same Excel file. What has been shared yesterday? Okay. So, it's a Excel file. I just click on the Excel workbook. Okay. Because in the case of a Tableau in public, you cannot save it. So, only in the desktop you can save it. In the case of public, you have to save it on the cloud. Okay. Only if in the case of table tab tablet uh desktop you have to save you can you have the option of saving it to the hard disk. Yeah. Fine. Hey we'll move ahead here. Hey see yesterday we just saw with the tables matrix and so on. In today's session we'll see about creating the charts. Okay. See very commonly used chart is what when you talk about a chart the very commonly used chart. So what is it is a column chart. Okay. So where the columns are been arranged side by side. So we will just go with the simple column chart. So if I have to go to the charts in the build option under the build okay or we can see that we have this particular what you say the charts option here. Okay. Um so I'll just select okay. All these are charts. Okay. All these are different different types of charts. We'll see some of these charts. Okay. Not all at least some of these most of the charts. Okay. U we'll just see the very commonly used is the column chart. I'll just select this. Okay. Hey when I take this particular column chart okay see in the charts we generally have what you say this axis is called as x-axis and um this one we call it as y-axis is it x-axis and y-axis. Now what is a column chart? What is a column chart? Okay, the column chart is nothing but a chart where each column represents a dimensions. Each column column represents its dimension and the length of this particular column represents the measurable value. So that means okay here um suppose if I say region wise sales regions are my dimension each column is going to represent individual region okay east, central, west and south region respectively. The length of that column will represent what is a measurable value they have. So if I say sales, how much sales has been done in the south region, how much sales is done in the west region, how much sales is done in the east region. So we can easily do a comparison based on the length of the bar. The taller is the bar is the higher is the value. Okay, the measurable value. So if I say sales, higher is the sales is higher is a uh longer is the bar so on. Okay. So based on that so when you select this particular column chart you can see in the build we get this option here called as x-axis and what do you call it as y-axis. We have the x-axis and the y-axis. So the this is the two basic things what is needed for creating the chart. Now your y-axis is a measurable value. So I'll just say y-axis I have to use a measurable value. What is measurable values? Yesterday we discussed about measurable values and numerical values. Okay, sales, profit, quantity, they are going to be the measurable values. So I will take the sales. When you take the sales here into the y-axis, you can see automatically a chart has been created which just tells me the total sales is 2.3 million. Okay, so one single bar has been created. So that means if I have to create a column chart the minimum requirement is we need to have at least one measurable value. Okay. Now we have the total sales but I want to see the sales for each region wise. I want to know okay how the west region has been performing, east region is performing, central region how the sales has been performing, south region I want to compare. Okay. So that means I want to divide this particular column into the region wise. So for that I'll just go to the x-axis. Here I said you have to use any dimension. So dimension can be region, segment, category, subcategory, states. It can be any discrete value. I'll take the region. So as soon as I say region here you can see we have the…

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