Power BI With AI Full Course 2026 | Learn Power BI With AI | Power BI With AI Tools | Simplilearn

What if you could take a simple Excel file, clean messy data, build powerful dashboard, track business performance, and even use AI to understand what your numbers are really saying. That is exactly what Microsoft PowerBI helps you do. Hey everyone, welcome to this Microsoft PowerBI and AI full course by Simply Learn. Businesses are not just only looking for people who can collect the data. They need professionals who can understand data, explain it clearly and use it to make smarter decisions. Sales teams use data to track revenue. Marketing team use data to measure campaigns. Finance team use data to check profit and cost. Operations team use the data to improve performance. But when all this data is stored in spreadsheets, reports and different systems, it can quickly become confusing. That is where PowerBI comes in. PowerBI helps you connect different data sources, clean and organize the data, create interactive dashboards, and present insights in a way that business teams can easily understand. And now with AI features like copilot, smart insight and natural language analysis, Pervi is becoming even more useful for faster reporting and smarter decision- making. In this course, we'll start off from the basics and slowly move towards the dashboards, visual interactivity, power query, data transformation, and AI powered analysis. So whether you are a beginner, a student, a working professional or someone planning to move into data analytics or business intelligence, this course will help you understand how PowerBI works from the ground up. By the end of this course, you will not just know how to create charts, you will understand how to turn raw business data into clear reports, useful dashboards, and meaningful insights. So let's get started. Also, just a quick information. If you're interested in boosting your career in business analysis, do not forget to check out the AI powered business analyst course. This course is perfect for professionals looking to enhance their skills with the latest tools like PowerBI, Excel, and SQL, all while gaining hands-on experience with real world projects. You will also learn how to leverage generative AI for smarter, faster decision making. Our program is IIBA, Babok, V3 aligned and helps you prepare for certifications like CBA and CCBA. You'll engage with 10 plus industry projects, 40 plus practical activities and benefit from live online sessions led by experts. Plus, with simply learns job assist, you will get the support you need to land your next big growth. The term itself talks about business. So business operation it's very important because when you understand the business creating the dashboard will not be an easy task. Understanding the business is also equal to understanding the data. BI or business intelligence it is referring to a technology or different tools or different processes of organization to analyze the data better. As I already mentioned people are taking decision by looking into the data. So to extract meaningful information from the data we are uh you know creating these dashboards. So business intelligence is nothing but the same business operation what we are doing manually. We are slowly moving towards a digitalized platform. We are making use of the AI technologies AI tools which is helping us to take our business to next level. It's very simple. I'll give you a very raw example. I can say before 25 years before when you go to a bank it was all manual. Even if you want to withdraw the cash, if you want to check the balance, everything was manual. We used to go to bank, stand in the tube, wait almost for more than two to three hours just to withdraw the cash. But today's generation where if you want to withdraw a cash, we have ATM option. I mean where we use credit card, debit card. But now people are not even going towards ATM. We all have online transactions available. We are slowly moving towards you know online platforms digitalized and AI tools integrated because data security is also very important because we are moving towards the digitalized platform. Data is getting generated maximum. We are using the same data maybe for future innovation or to have a very good experience or to generate new such tools to enhance the knowledge and also to retain customer in this domain. We are working with the data. We are analyzing the data. We are visualizing the data to move towards you know to you know to move towards AI not only AI trend but also to create uh you know a safer environment for all customers to use the application it's all about understanding the business understanding the data creating the dashboard if I talk in words so improving the for improving the operation for identifying the trend for gaining a competitive edge out of all other competitors see If you give a very good survey, customer will come back to you for sure. If you understand the customer better with the different trend, what is the trend of customers, how the sales are running from so many years, how can I manage you know the products, how can I manage the supply chain, for everything we need a data to take a decision, we need a data. So that's what the business intelligence all about in a nutshell. You have a data from a domain that is maybe a net banking or a banking domain. You have a data with you. So you are creating a dashboard out of it to understand your customer of the banking better. It is very simple example. So to concentrate on business intelligence there are few key components which we need to understand that is nothing but working with the data is very important. Then I say I work with the data. From where are we getting the data? From where we are collecting the data. Data is collected everywhere. Websites are collecting the data. You are if you want to use an application, you will register yourself. Data is getting generated. Almost 95% of data is getting generated with this online platform. gathering data from various sources including internal system, external databases, social media platforms. This involves identifying relevant data sources and developing strategies to collect and store the data efficiently. For us to work with the data, we are collecting the data from different sources. We will clean the data. I mean after collecting, of course, we need to clean the data and we are getting data from different sources. We will collect it. We will import the data to PowerBI and we will create a dashboard out of it. Data is collected from different sources. I can say and I can see some question in the chat. PowerBI will only work for No, no, no. Not only banking domain. PowerBI works on supply chain. PowerBI works very well with e-commerce, banking industries, all government officials, IT, nonIT, all companies can go and make use of PowerBI. If yes then how for healthcare domain it is important to answer this question uh almost two years back I was working in a healthare domain uh it was a company was related to healthcare domain only so there we are there we were using powerbi tool just to maintain the health care product the cost of healthare product if a customer is buying one product what is the cost if a customer is ordering in bulk then what discount I'm giving to them if customer is very important to me. If customer is engaged with me from past 5 years, I can give them a good discount. I need to give a very good customer service to retain the customer and I want customer to buy product from me only. When I talk about healthcare industry, see uh the healthare industry means chemicals, medicines, there are so many products which will be you know produced and that product shelf life will also be there to understand the shelf life of the product to maintain the customer data if they're buying in bulk. See especially the product no like 0.5 I mean.5 ml.5 mg 1 mg 2 mg there are so many products I can say personally I work on nine lakhs of product just for one customer they are ordering nine lakhs of product with the minute change in the dilution I can say the chemical dilution and the the complete nine lakh products and the cost of it the discounts of it in discounts also there are so many types discounts which internally will be given. Uh so I mean all these are depending on different companies to be honest as per my experience I'm just mentioning what I experience with the LTL domain. So giving them different discounts. So maintaining this data and giving this data to a customer for them to understand clearly for them to understand cost of each product clearly you can prepare a dashboard. You can discuss that with your stakeholder that means your uh customer and you can give them the complete insights one best you are giving to them with the help of dashboard. Especially for stakeholder management this tool is needed maximum. So healthcare domain or supply chain or biotech even government officials all the industries can maintain data can represent the data using this PowerBI tool. Data integration as I already mentioned data will be available in different formats. Always PowerBI considers structured data or tabular data. When the data is in structured form, when the data is in a tabular format, structured or tabular, the meaning is same. When the data is in structured format, then only you can take that data to create a dashboard out of it or to create a visual out of it. So maintaining data format is also important. Imagine when the data quality is not correct. Of course, we cannot expect a good result from the dashboard. dashboard what you created with uh low quality data will always you know will always create trouble for you to take a good decision. So it is very important to maintain the quality data structured data to get a very good result at the end because dashboard should not give you some incorrect data. Dashboard completely depends upon your data. The graph what you're creating each graph you know they have their own uh you know principles as for the principle you need to select the data if data itself is not correct if data itself is not good you cannot expect a good result at the end so working with the data data formats resolving inconsistency and creating a unified view of the data is very important in a nutshell you are preparing a dashboard to check all the answers at a time in one shot unified view I can say but if data itself is not not correct you cannot expect a good result all the graphs will be affected not only one graph everything will be affected there yeah so data storage we already know data storage again it is expensive and companies are spending lot on data storage itself to store the data we have cloud platforms We also have a different data centers available where each company stores their data there by paying and here organizing the data especially structured data is very important. This ensures the data is easily retrievable and protected from loss or corruption there. I mean cloud platform are storing all the data whenever you want you can extract it. So data storage again is very important. And when I talk about data analysis using statistical techniques, the data mining and machine learning to uncover patterns and trends in the data. This involves applying analytical methods to extract meaningful insight. For a business analyst uh group, data analysis is also a part of it. When you understand the domain, you can easily understand the data. So we have so many techniques which we can implement on the data to extract meaningful information for me to understand uh you know the data better. Right now I'm using PowerBI to extract meaningful information from the data. If you are using Python you will go with different libraries to uncover the pattern to understand the data. You use different Python libraries to understand. Now we are going with PowerBI. What what how PowerBI helps us? It helps us by creating the graphical representation of the same data. You can analyze the data in multiple ways. Not only with PowerBI using different coding language also you can analyze the data just using Microsoft Excel also you can understand the data you can analyze the data. Multiple options we have right now we are depending on PowerBI to understand and to visualize the data. two options we have with this PowerBI for a BA role also we need a Python skill map. Yes, it is important for a business analyst also to concentrate on Python programming language. So let us continue with the next topics that is data visualization and reporting. You already know I have mentioned it multiple times data data data then data visualization. So you are creating different graphs all together combined as a dashboard. This helps stakeholders to easily comprehend complex data and make informed decisions. You have a raw Excel sheet data. You will give that to your stakeholder. Will you think that your stakeholder will check each and every row in that Excel sheet? Of course no stakeholder will not do that because they are your stakeholders. You need to give them a very good surveys. They expect you to upgrade yourself with the different options available in market where you are depending on PowerBI now to create a dashboard for stakehold not only stakeholders for you also it is easy to clearly understand the data in the pictorial form. Generating reports that summarize key findings and insight. This involves creating structured documents or presentations that communicate the results of data analysis in a concise and effective manner. See data creation I mean not only about data visualization for you to move towards data visualization before you move towards the graphical representation data will be available in the form of report. We have a report view in data I mean in the PowerBI where you can clearly see the complete data in a structured format that will help you to create a data vision. So I will show you all these one by one. Don't get confused. Dashboard is nothing but adding all different graphs together. Even if you uh you know change if you add some filter if you change one graph all other graphs will be automatically filtered as per the change what you did that is called as a dashboard. Report is nothing but the before you create these graphs before you create this dashboard the data will be available in a tabular format in a structured format that is called as data report. So business intelligence advantages you can see as I already mentioned. Yes, this for decision making it will be very helpful to increase the efficiency and also productivity to understand the data crystal clear. This is helping us. Customer satisfaction is important. When you give a good service to customer they will again come back. So this will help you to understand data which is also equals to understanding the customer understanding the business competitive edge again to move forward with advanced technology industry use cases of BI. Now you can clearly see different industry how they are using the data sales analysis of course business operations sales team how sales team uses BI for them to track the sales for to check whether they have achieved the target or not to understand what customer uh you know expecting what are the products they're expecting what are the top selling products what are the least selling products reviews on the products sales team will concentrate on the entire end to end sales data I can say coming to finance financial reporting so here they concentrate more on revenue finance economy I can say so generating financial statements analyzing the profitability of the business or loss it will be taken care by the finance team so end to end about you know finance it will be taken again but that team will be taken care and they are using powerbi to showcase the team marketing analytics to understand uh the customer recommendation is very important and that's one of the important topic when I mention AI recommendation system you are searching something on Google you will find multiple options on Instagram how it is possible sorry so so we were discussing on the advantages It is used in market. It is used uh you know PowerBI is used with uh marketing team also. HR also depending on PowerBI to understand the employee and how the employees working, how the project is running, everything can be analyzed, supply chain management. So not only these five teams apart from this everyone can depend on PowerBI to showcase their data. So what is data analysis? Now so far you know how your company works. you are working for a e-commerce or any platforms you're working for different companies not at all an issue first thing is you need to know how your organization is working just a second so we have multiple steps one by one I will write here so this is the first step where business understanding is important so business understanding is important with this business understanding knowledge this is the first step you will move towards data This is your second phase. This is your first phase where you will move towards the data analysis DA which I can say you need to correlate your business questions to this data. For example, you're working in a e-commerce platform. They are expecting you to extract some meaningful information from the data by listing some questions. They're giving you around five questions. You need to understand the business first. You need to understand these questions. To these questions, you need to use this data to answer. So understanding business, understanding the questions, these questions are related to business only. Business operation questions only. But to you need to answer this question using this data. So business operation, business understanding and then your data understanding or data analysis. the this is the important part I mean all the steps are important here you will spend maximum of your time I can say 60 to 70% of your time you will be spending in analyzing and working with data when I say data analysis uh sorry I will just uh write here when I talk about data analysis data structure, maintaining the data structure if required, data transformation. And then the third step is to check the data quality. When you're checking the data quality, it is also checking the data type or data format. You can call see different technical terms but sometimes the meaning is same. Okay. So data format check and then comes in lame it is about understanding the data. Okay. So what are you understanding in data? You are checking the data structure. You are going with the data transformation. You will understand the data quality where you will concentrate on data type, data format and then you will move towards I mean data structure, data transformation, data quality and then understanding graphs as per the data what you have that is nothing but which we call data visualization principles. So these are the sorry yeah these are the important these are the important points which we will consider when we are doing a data analysis checking the data structure going with the data transformation. Data transformation is when the data is not structured or if you want to do in uh one. So data transformation is also about adding or modifying the data or it can also be removing the existing data. Not only adding it also removing existing data. Data transformation is also where we concentrate on modifying the existing data removing the data adding the new records to it. positive in PowerBI. Once you grab the data based on calculations, you can add new column or new row or appending the column which we call you can also removing the existing column. Adding removing you have both the options. So you can only do this when you understand the data when you understand what is your project or when you understand the business questions properly and then you will move towards the dashboard preparation whereas you need to know the data visualization principle just is statistical knowledge required here yes analytical skill an analytical knowledge will help you to understand these concepts better related to powerbi whatever that we have I will explaining you but additionally if you already have a good knowledge on stats it will really be a advantage I can say hope this is clear so it is all about examining the data and other important tip I want to mention based on my experience your mindset should be a research mindset when you're working with data now you might have observed that your mindset should be a research mindset where you will research only with the data you will go out to do the research like cops but you will sit you will alone do the research with your own data to understand it better. So research mindset research analytics itself a separate topic for you to work with the data. So research mindset analytical skills the decision making problem solving these are some soft skills or non-technical skills which I can say which is important for you to carry in this journey. Whatever the steps I mentioned no the same steps is mentioned you know uh added here data collection data cleaning data exploration data transformation and data modeling data visual I think data modeling is something new which I didn't mention before so here let me just check so this is about data collection the first stage you know what is what is the purpose of creating the dashboard. You know what are the questions you need to answer. So you have the data you collected the data which you need to consider to answer the questions. You need to go with the data. You need to explore the data. This this is also called as descriptive data analytics. I think I can write here. This is also called as data exploration where you will do in-depth research on the data. See, I'm using so many technical terms. Please don't get confused. If you have any questions, please let me know so I can help you. Data exploration is indepth doing the analysis of the data also called as descriptive data analytics. And one more important point always you will work with the past data. I can tell you what happened yesterday. I can tell you what happened today morning but I can't tell you what will happen tomorrow morning. Always the data what you use to prepare dashboards or any project machine learning AI or any projects you work you will always work only with the past Future prediction will be taken care by the model. Especially this PowerBI tab view dashboards you build you are building on top of past data which is helping you to take a future decision and for future prediction this data is helping you to understand the future prediction I can say. So always working with the past data. So data transformation again if you want to do any data transformation do any data changes adding removing that is also possible in data I mean that's this uh you know stage of data transformation and then data modeling data modeling is nothing but you can merge data from different sources okay that means one excel sheet will have multiple tabs I hope you all observed it one Excel sheet can contain multiple tabs. One tab can be related to another tab. Imagine customer details you have. I will just write here. Please understand the concept. Customer details you have. What are what's the main important uh data which you can add in customer details that is customer ID. Customer ID is one of the important I'm so sorry if I will write again. When I talk about customer data, the important for you know data what you can expect here is customer ID. Customer with this customer ID it's a unique ID given to each customer where you can check the entire customer details. Imagine you also have the order ID in order ID. Sorry, order data. In this order data you will have customer ID who ordered that order I mean who placed that order. So customer ID will be there and order ID will be there. Sorry, order ID will also be here. Using order ID you can check sorry using customer ID you can check what is the order being placed. So you can merge this customer ID and this customer ID you can create a link between two data sources using the common uh you know using the common column. This is what we do in SQL. We will try to merge the data by considering certain common column especially the unique column what we will be considering to merge the tables. So that when you merge the data now you will the new uh data model will be created or the new data set or the report will be created where you can see customer details and order details together. That is by writing a query you can merge. You already know about I mean if you know SQL you will be knowing uh you know joins like right join, left join, outer join, inner join. So we can also do all these modifications in PowerBI. We can write a query and we can merge the data together. Data model is nothing but you will have multiple data sources where you can combine them together and you can create a dashboard out of it. You no need to create for each data different dashboard. One dashboard can give you the information of multiple dashboard. Sorry, multiple data joins using unique ID primary key. Exactly. So we have the different join where we will be merging the data with this unique ID which uh we can consider maybe the order ID or customer ID based on the customer details. So SQL is also integrated with PowerBI but not exact SQL code. The code or the query will be almost similar to SQL. That is where the data model I will show you all these. Please don't mind. I'm you know speaking so much today than showing you online. Please don't mind. Please make a note on these steps for sure. We will be working on all these topics. Next comes the data visualization. After allation you are showcasing the data in terms of data vision I mean creating the dashboard. This is the complete step which you need to concentrate when you're working uh with the data especially with PowerBI or Tableau. Even if you're working with Tableau the stages are things only thing is you are using a different tool. You can also use Microsoft Excel to create a dashboard. Uh I think you already know about it or you might have created if not please understand the graph what you are creating the dashboard what you are creating in PowerBI you also have an option to create in Microsoft Excel but the efficiency will be low efficiency will be low manual task will be high you and Excel will of course sometimes it will hang when you have large amounts of data Excel will not you know work I mean Excel will not open properly it will And sometimes efficiency will be low. It will work similar not exactly the same but similar task you know it will help us to uh create a dashboard using Excel but it is not like which is I mean you cannot expect a good efficiency out of it. So let us look each step in detail. As I already explained data collection is sources or from different portals or from your company. If your company is an e-commerce company, you need to understand the e-commerce how the business work. You need to collect the relevant data. Data cleaning identifying and correcting errors, inconsistency or the missing values. Data exploration where you will do in-depth data analysis that is also called as descriptive data analytics data transformation converting the data formats adding removing it is also possible data modeling. See data model is not only about creating a link between the data models. If you want to move towards an advanced technology, you can go with the machine learning model to predict for you with this dashboard. You can see the picture. But if you want to know the exact prediction, you can also make use of machine learning algorithms which we have with respect to Python code. We have certain libraries which will help you to create a machine learning algorithm. So with that also you can do a prediction. See multiple topics are integrated here. So creating dashboard I mean data visualization is nothing but creating a visual representation of data like graphs, charts, dashboards. Descriptive data analytics, diagnostic analytics, predictive analytics, descriptive analytics are the four important types of data analytics. See it's very simple. Descriptive analytics is all I mean I will write here the the pages. First thing is you will always have a past data with you. With this past data you can clearly understand what was the sales in 2024 because 2024 is done. You're also about to complete 2025. Now you have a 2024 sales data. your manager gave you sales data of 2024 where the target by the end of December it was closer to 2CR. This is the revenue generated after removing all uh you know uh the investment. This is the profit generated. Okay, profit generated. I can mention now your manager gave you this data. You are in a critical situation right now because it is November 2025 where after removing all the investment it was possible for us to reach only 1.5 cr only 1.5 cr every year we try to improve our we want to grow we want to improve nobody expects you know to have a very nice scale nobody expects to reduce you know or reduction in the sales or revenue. We don't expect it. We always work and we want every time to see something which is good. We want to grow the organization by default. So he gave you the data instantly and he want at least to achieve the sales as same as 2024. Even though it is not possible to reach more than 2C crs to reach at least until 2C cr he's giving you a debt target which you within one and a half month within you know 40 days uh reaching 50 lakh he is giving you a data and he's making you to understand what was earlier sales how the sales was running what impacted the increase in the sales last year why it is getting decreased In this year multiple analysis can be done. Why it was 2CR? Descriptive analytics is all about working with the historical data to understand the pattern to understand relationship to understand the entire sales of 2024. You need to concentrate on the past data and that is called as descriptive analytics. You will use different statistical methods. You will check you know for example uh the sales was related to pizza. So you need to understand the sales of 2024 pizza sales. Which pizza sold maximum and what is the uh you know what strategy did they use to uh sell maximum pizza and what was the cost? Uh when the customer purchased maximum pizza, which month contributed maximum, why that month contributed maximum. So all the analysis we are doing here. Descriptive analytics is all about identifying understanding the past data. If I move to diagnostic analytics with the results what you get from descriptive analytics you will go with the indepth research on the same data to understand the insights. I will just stop stop coming here and I will diagnostic analytics is all about you got to know what uh you know in which month it was maximum which product or which pizza we sold maximum you have all the insights now you will go with the deep investigation internally to check each and every record each and every data investigating you know the here the investigation level is 50% maybe here The investigation level is more than 100%. First you will extract some of the important information to answer your project. Later for you to see not every time you are you will find the sufficient answer in the first step. You need to understand you need to check data multiple times where you will get the maximum insight. So extracting maximum insights from the data we call that as a diagnostic analysis. Please remember when you're working with PowerBI or maybe a business analyst role, data analyst role, not at all an issue. You need to understand all these types. You can expect interview questions on this for sure. What are the stages? How the stages helps us to create a dashboard. You can expect all this predictive analytics. Based on the investigation what you do in stage one and stage two, you will move towards the prediction. prediction. You can either do the prediction with this dashboard by predicting what are the possible fees. This is your actual data. This is your actual data because in both the stages you are working with the past data which already happened and this is your actual data. This is your model predicted data. I can say this is just a prediction. this prediction may be true or may not be true. the situation the results what you're getting from this prediction though it can be true or may not also so whenever I talk about prediction it's just the meaning itself the term itself says it's a prediction it's not the actual scenario it's not the actual data it's just a prediction which is helping you to which is helping you to have a very good knowledge also for you to prepare for future this predictive analytics will help you Prediction or predictive analytics is all about future prediction with respect to past data. Then comes prescriptive analytics. You predicted for future. Now you need to understand to reach the target. You are getting a prediction that you can reach the sales of 1.9 cr within next 40 days. You are right now in 1.5 cr. 40 lakh you can increase within next 40 days that's the prediction what you are getting to reach the target what necessary actions or decisions you need to take that is called as prescriptive analytics after you build a dashboard your task will not end to be honest your task will start once you build the dashboard you will discuss that with your stakeholder these are the possible strategies which I absorbed from the past data and with the prediction I can say that these strategies will help us to reach a near target of 2C cr you can either reach this target of 1.9 cr or even if you stop at 1.7 cr not an issue but this is just a prediction you cannot 100% depend on this prediction you may go higher than this or it may be lower than increase you can also it can also increase or it can also decrease. So step by step these are the stages which we consider whenever you work see not only with PowerBI these stages will help you any tool you use if you are working with data please consider on these four analysis after this there is one more analysis called as cognitive analytics where after you build this prediction and prescriptive you can make use of machine learning models and AI models and make your machine to learn this data for further more benefit. analytics that is called as cognitive analytics where you depend on AI techniques. So when I talk in terms of business imagine you're working under a business operation team. So what is your main goal or main target? Business operation means yes you need to give a very good service to customer sat satisfaction and again you need to run multiple ads to gain customer attention. Marketing strategies decisions will you will be able to take with this different analysis what you will use with respect to data. All these analysis are different steps in analyzing the data. Exactly. All the steps whatever I'm just mentioning here, these are the four important analysis or also called as analytics which you will be implementing on data step by step. So healthare industry analyzing the patient data. Healthcare industry takes the data of patient and it will help doctors or physicians to understand the data why customers are coming back which tablet is working which tablet is not working which is the advanced one treatments outcomes improving you know the health care industry is uh uh you know it's a big impact I can say because even though if there is a minute change in the prediction it will affect patients health so healthcare industry means please be very careful the data of QRS is uh you know with high uh you know it's like high end I can say to talk about finance predicting market trends accessing risk and managing the investment stock market analysis is one such good example uh which will give you a clear idea on how to understand the stock stock data where to invest where not to invest you will get the entire your prediction and let me tell you all stock market platforms are using the AI techniques or are the dashboards what you can see if you are working with I mean if you're using the stock applications like grow or share card I personally use that so I'm just giving you that name there are so many platforms where you can see the chart you can see the dashboard you can see the numbers in percentage or you can also see the actual value plus or minus all the predictions are applying just with the help of data stock market is one good example when it comes to banking industry or when it comes to economy I can say coming to science again without science without engineers it's not possible to do with all this discovering new patterns and in fact in scientific research any industry you work not only these four all the industries are behind data everywhere data is collected you need to remember the four important analytics to move forward again the entire stages whatever I mentioned so far preparing the data data modeling data visualizing sorry preparing the data governing it I mean sorry maintaining it clearing it and data quality data structure data governance it is also called as data management again The terms are almost same. The task will be same. Analyzing it, preparing a visual as per the requirement, data modeling, all the topics are important. As a data analyst or as a business analyst or as a PowerBI report developer, you will be concentrating on the entire topic. Starting with the PowerBI tool, a business intelligence tool developed by uh you know Microsoft. Most of the organizations are behind this PowerBI which we are again learning. So let us quickly start. This is how your application looks like. The PowerBI application looks like. This is the homepage of PowerBI. a business intelligence tool, a platform that allows you to connect to various data sources for data transformation and also for report building and to share insights with your team or with your stakeholders or with anyone. You are using this dashboard to represent your This helps users to connect the various sources also for cleaning purpose. This platform's core function is to enable organization to make a better datadriven decision by providing clear and a useful information. If you give some uh you know information which is incorrect there is no point and it will see whatever dashboard you create no especially in a company multiple teams will use the dashboard. One wrong data will affect multiple teams performance. So the main key functions of this PowerBI is the data collection, data preparation, data sorry so data preparation first the data connection then data preparation, data transformation, data visualization and then comes your data analysis and then preparing the dashboard and then sharing kind of people. This is how it looks. I hope you already know about it. How it looks and other things. So step by step we are going. You can see the key features data connectivity, data transformation, modeling, the mobile access, report creation, dashboard creation and the newly added AI features that is natural language query. you have an automatic Q&A option or a chatbot option available when you create a dashboard. So it will help you uh you know to I mean whatever the data you leave your I mean whatever data you use to create the dashboard no that will be taken care by the powerbi you can ask any questions using this Q&A it will answer I mean the powerbi dashboard what you created will answer the questions by reading the data itself that's a features which is added the key features of powerbi or you can also consider as an advantage Benefits of PowerBI as you already know efficiency, productivity, collaboration with multiple teams by sharing the data in a centralized platform, scalability of handling large data set. Complex analysis can be done using this availability, data availability and also you can use it even in your mobile phone also to check or to refresh your graph to check the insights. You may not be able to create how you create in your desktop but it is also you can also access it in your phone and you can check the view I mean you can view it you can check the results improve decision making enhanced collaboration productivity availability and scalability any questions you have please let me know because I know these topics are quite similar I think we have already discussed on all is but still if you have any questions please let me know. These are the three options what we have with PowerBI. One is the desktop version, PowerBI service, PowerBI mobile. This service is paid version. Uh this service is used by organization where people will use the different options or they will create a dashboard using this PowerBI service and they can share the dashboard with other people. The way you use PowerBI desktop, it is almost the same but it is with respect to server where it is all completely managed by a company and data sources will be there, databases will be there. There are different servers which is maintaining this dashboard. The way you create the dashboard is same everywhere. Don't get confused. What if you are not using PowerBI service? So it is the same. Only thing is like it's a tool what you are using right now. Later maybe in your company you will use a website like a server. PowerBI desktop is what you all will be downloading to your laptop or a desktop to use it and also to create dashboards to do the data transformation and all the options whatever you have with PowerBI you can do it using the PowerBI desktop download. after downloading it in this PowerBI mobile see when it's mobile phone you can view the data you cannot do any uh you know you cannot create a dashboard like how you created laptop that everyone know because it will be clumsy when you use the mobile phone it is good to view so the three options what powerbi is offering so this is how the powerbi desktop looks this is a primary tool for creating and developing reports and dashboard It offers a rich set of features for data cleaning, data transformation, modeling and also for visualization. So this is you will be creating similar dashboards. So right now please understand I will make all of you to get answer and experience. Please don't mind because today's agenda is quite different. Tomorrow's agenda is very interesting where we of course get experience on uh you know this tool. This tool available in paid version also free version also you are downloading the free version please don't go with the paid version but if you're working in any company and if you have a paid version you can utilize it this is how your powerbi service looks it will be a server based application I can say and this is only available for organization this is online cloud-based platform of powerbi where you can publish share View, edit, collaborate with people with the status. This is only paid version. The way you create the graph here is as same as the way you create the graph here also. Only thing is two different applications. This is mobile access with PowerBI mobile. This mobile app enables you to view and interact with your PowerBI content on your smartphone or tablet. This is the PowerBI architecture. You will get the data from different sources. Data can be internally in your laptop like an Excel sheet data or you may grab the data from a database from a physical database or a cloud platform which is an online database or you can have the data in text format. So different data sources will be used to create a dashboard and this can be again created in PowerBI service or PowerBI mobile phone also you can do this is how it works the step by step I can say grabbing the data creating a dashboard but before you create a dashboard you know the several steps there and the visualizing it this is the architecture of PowerBI with the multiple uh you know services what they have semantic model and visualization the building block see there are two important points here one is the static dashboard and one another one is dynamic dashboard I think that is not mentioned here not an issue I will write here what is the difference between static dashboard and dynamic dashboard this is applicable uh for all the you know tools whether you use excel or you go with python board or you go with tabular view powerbi it doesn't matter there's a dashboard called as static dashboard or dynamic dashboard the name itself says dynamic dashboard is nothing but okay first one one by one moment static dashboard is where you will create a dashboard only once which is not been updated like you cannot update the same dashboard because it is only with a limited data and you are not doing any automation you can do the automation but When I say static dashboard, you are not updating or you are not automating it. That's the meaning of static dashboard. Dynamic dashboard is where you will do automation. As the new data becomes available, the graphs are updated automatically. Automatic graph updation unlimited. So these are the two technical terms. When you are creating a dashboard, people may ask you is this a static or a dynamic? Static means which is stagnant. Uh the graph will not be updated. It's only with the data what you imported. See you have uh thousand lines of data in this Excel sheet. You will import it. You will create a visual. You share it with people. That's it. This data is not getting updated. But when you want to go with dynamic dashboard, you have today thousand customer details. Tomorrow again new customers will be adding or the same customer will be purchasing something new data will be adding up right so that's a dynamic dashboard which you create you will link the same dynamic data you will create a dashboard automatically it will be adding up with the new records when you go with the refresh visual option I will show you all this please don't mind I'm giving you enough information now please make a note we'll work on all these topics I will show you how you can do automation with Excel. How you can do automation with database for static dashboard is where with the available thousand record you will use the same Excel sheet you will import it you are creating a dashboard your dog your job is done you share it with stakeholder stakeholder will understand these thousand customer details only data will be limited only these thousand customer data you are giving to your stakeholder the new data is available today. See until yesterday you created a dashboard. What about today's data and what about tomorrow's data? The data will be available. You have 2024 dashboard. But 2025 we are already in we are already in November. You don't you don't have the data available in the dashboard of 2025 because it is static dashboard. You made your dashboard only to learn the thousand records of 2024. automatically it is not getting updated. where man you need to go again you need to create a new dashboard you need to import the data you need to do all the manual task again the same dashboard you're creating you are not upgrading the same dashboard when you when you're working with a static dashboard no you're not upgrading the same dashboard you are not doing any automation here but when I talk about dynamic dashboard 2024 you created that's for the same dashboard you are giving new records you are giving 2025 data also same dashboard is getting upgraded you make your dashboard to learn the new record you are not creating another dashboard so static in the sense which is stagnant which will be changed which will not be modified again and again dynamic is where it will be keep on changing you can link multiple data sources to one dashboard mode. So that's the one which I mentioned earlier. Multiple data sources you can link together and you can prepare a dashboard out of it. One dashboard you can create this. That's what semantic models and visualization are the main building block of PowerBI. You can expect questions like interview questions like what is the architecture of PowerBI? What are the stages involved in creating a dashboard in PowerBI? What are the building blocks in PowerBI? Can we do automation? For that you can give an example of static and dynamic. So now talk about the block semantic models and visual. So semantic model is nothing but we have multiple views in PowerBI that is report view, data view, uh visualization. So we have so many options. Semantic models are nothing but the DAX quin or data model or the report view data transformation data cleaning the back side. Before you create a beautiful dashboard lot of work we will be doing in the back end that is called as semantic model. Collecting the data, transforming the data, cleaning the data, checking the relationship between the data it is called as semantic model. When I talk about visualization, visualization is all about creating a dashboard, creating an interactive dashboard. The outer layer what we what you will share it with your stakeholders. So it's the outer part of it. You will not show the inner part the complete the work whatever you do all the match you will not show to people. You will only show the presentation the proper dashboard the outer part inner part you will not show. So that is your schematic model is your inner part where you work where you work with the data transformation creation will be taken care visualization is where creating a dashboard out of it. It's very simple uh powerbi empowering the data analysis of course powerbi see this icon is nothing but a combination of python and a powerbi. So PowerBI not only Python will help you or not only Excel will support you or not just other tools. PowerBI is giving you a very good uh analysis or uh you know very good analysis you can create with respect to data uh deeper analysis you can do. Earlier there was no concept of DAX query or power query but now it is integrated with PowerBI. I mean from few years we have almost from two three years we have but before that it was only dashboard uh query option was quite less now advanced query options we have additional graphs are getting added every now and then and every 6 months the version will also be added the new versions will be getting so simplifying the data preparation data accessible is easy because 99 plus data sources options we have enabling visualization exploration. This is your diagnostic analytics. Facilitating the deeper analysis is also possible. Empowering data analysis with all the key concepts. So let us quickly download the powerbi tool. I will give you I will share the link. I I'm checking I'm opening a Microsoft store. If you have Windows, this is one such method in which you can use to download the Microsoft application just type PowerBI. How you download application to your mobile phone? No, how you use in your mobile phone uh you know the app store or Google store to download the application in a similar way open Microsoft store in your laptop or a desktop and then download it. I will uh al I mean in Mac also you can directly go and check the applications or I I don't I have not used Mac but please check your app store you can see you will be able to download PowerBI I think right now it is not available paid version is available I believe from people who are using Mac I will share you the link which you can download I don't think so you have an application but if you have it please download So Microsoft desktop I already installed. So it is uh showing install. Don't go with this PowerBI report builder. This is for report purpose. This we are not using this. We are using PowerBI desktop directly. Download it. Let me see if I can I will share the link in the chat. All of you please use this link to download. This is one link. I will share you another link also. This is this is the link which belongs to Microsoft store. You can directly download you can explore it's a very simple you can explore the tool same whatever I explain the same points you will see here I have given enough information on the application and why are we using this powerbi I believe you all are on the same path you can explore this I have already downloaded so it is asking me to open this is One such way to download people who are using Mac go and use the link which I'm sharing right now. Second link official Microsoft PowerBI website which will help you to download Microsoft the PowerBI application. It's a userfriendly free to download. Please don't pay anything for it. This is pro. We are not going with this pro. Please don't buy. This is one link which you can use to download. Another link we have I believe. Don't go and use any third party links to download. I will share another link. You can go with these three options. Please don't go with third party link like you can see here. I think this is PowerBI only but this is server uh you will not be able to download this only work for people who have paid version. So don't go with this and don't go with any of these applications apart from Microsoft. See this option you have. I hope you can see my screen. You can see this Microsoft PowerBI which you can download for your iPhone. PowerBI service is available available for people who are using Mac. But PowerBI free option what we have though that is not available. Hope you all can see my screen. Please don't sign in. Without signing in, you will be able to work. Please don't sign in. I hope you all can uh see my screen. This is how it looks after you download. No, it's not. If it is not, then you have then you might have downloaded uh the other third party one. I think see that's what I'm telling. You will not be able to download or use PowerBI desktop in Mac. for Mac only paid versions are available. So PowerBI service which I mentioned that is available. So for you to work if you have an iPhone and it supports you, you can download it to your iPhone. But again that is only to view. So so far it is not possible for people who are using Mac to use this free option because this free version is available for people who are using Windows not for Mac. For Mac you need organization account only or you need the service one. Hope all of you can see this uh PowerBI desktop. Can I use service fund for practicing? For sure you can use the service fund for practicing but I think it may ask you to pay something. Please check once uh you will be able to uh understand what exactly it required but uh it's not available for you to download like how famous people are downloading. So I'm just opening the blank report. I didn't save yesterday's one. So I'm opening the blank report and it was a CSV file which I sent you yesterday. So CSV file what I just want to import that is the patient data. I'm importing the file. It's a CSV file. This is how to import. You already know that. So this is the data what we have. You can see we have eight to there is a value which is missing and you can see a different data type. So replacing the value, replacing the null value and doing modifications you already know. So now we are concentrating on how to change the data type. We have so many options. I will show you all the options one by one. First with respect to powerbi I will show you already know the changes how to do in power query. Today I'm showing in both I can say this is the data transformation step. Okay. So this is your date sorry data pane and this is your visualization pane. This is your filter pane. So here you can see the table view of the data. So here also in case of table view you will be able to do the data modification like you can create a new column based on the measure. I will show you that. But we are concentrating on data transformation especially with this column. One by one I will show you. As soon as you select the particular column, you can see the patient ID. That's the column name. If you want to change the column name, here you can do or double click on the C also you can do. And you can see it's a old number. If you want to convert that to a decimal number, you can convert that to a decimal number. It is asking you with this data type. Your data will be stored differently. This will cause a loss of data or precision. After you make this change, you can restore the column by refreshing the table. So now it got changed to a decimal number data type. If you want to convert that to text, now you see it is getting converted to a text. So this is already in text data type. This is a old number. This is a text. This is again a text. This is also a text. This again it's a text but this as you can see treatment date it's a date time data type what we usually have to understand uh you know what was the treatment date of that particular customer customer's treatment date I can say you need to convert you just want to do this modification so see if you want to see the date time data type combination of date and a time together then you can use this option to do the changes this comes See and first you need to come to table view select the column then you will get this column tools here you can do the modifications now so now I just want to convert this to a date type yes now automatically you can see the data transformation is happening it's a right alignment of data with both date and time together so this This is one method in which you can do changes with respect to date time data type. And another one date. If you don't want to go with date and time together, if you only want to see the date, you can convert it. But you can see the format. What you're expecting is different here. See here it is. So what exactly you want to see? Do you want to say the date, short date, long date or dd mm? Y. So whatever the data how you want to store it you can go ahead and select it. I just want to go date month year. Now you can see the proper alignment of data which is getting converted to dd mm y by y. This is how we will do the data transformation in powerbi. Hope this is clear. Here you can see it's not only that you need to do here after selecting you can come to the format and you can see the multiple options what you have. This is a method in which you can exactly get the format and do remember an important tip here. This date time data type is also aligned with your laptop or maybe a desktop what you're using that date data type also should be aligned properly. If not that is the system issue which usually occurs. See sort by column. How you want to sort the column? So sorting is nothing but you can sort the column based on particular column names. You want to sort based on gender. See based on gender and I selected the treatment outcome column. If you select this column, sort by column, sort by patient name. We can't sort gender column by patient name. There can't be more than one value in patient name. So this sort is not possible. Come here. Sort based on patient name. Usually numerical data and then a categorical data what we consider. So if you want to sort age based on diagnosis. Now you can see data group. So new data groups you can select. So if you want to prepare a new group of data then you can select this option. This is this bins is nothing but the size of the data what you want to store. See that I selected age column and I group the data here. This is one of the option to copy paste it and but this is a bins now. So age of bins if you want to add any new measure to it we will first copy that it is called as bins and then you can measure it you can create a new column out of it or you can delete it. This is as same as what we do in power query to take a duplicate of it. We will do it with respect to bins in case of powerbi. Okay. Okay. So what I did is uh in the last call like yesterday's call we know we just copy pasted a column that means we copied and we pasted it was a duplicate which was you know which we learned in yesterday's call but now you cannot copy and paste a column like what we do in power query. This is your normal PowerBI. I'm going with this table view option and I'm doing modifications for my for the column like the same yesterday there was an issue with the date and data type and I mentioned you that we'll be discussing that today. So we are discussing on that and I showed you the changes. Now the data is perfectly aligned. What other options we have with respect to this table view is to sort the column. So you're sorting the column based on certain measures. Usually you need to consider one categorical data or maybe based on the numerical data you will be sorting it that we discussed here to talk about data group. If you want to create a data group create a new group of new group to combine multiple values into one. So I selected a treatment date that is called as treatment date bins. Do you want to store it as a list or do you want to store it as a bin? It will be asked here. If you go with the list for first I will show you bin only. I will show you one by one. So first let us see how we can create bin. Number of bins. So minimum value, maximum value, bin count is four. And then if you go with open you can see here a bin is nothing but the same data is copied. The same original data. I selected this treatment date column and I created a bin out of it. Like you can see here, this is a bin. Whatever the calculations you want to do, if you want to do it, if you don't want to do it on the original data, you will take a copy of that directly. Ctrl Ctrl V is not possible in case of table view. That is your Power Query. This is with respect to PowerBI. You have a table view where you're copying and pasting the bits. I will delete it. Now see it's nothing but the same data you copied. It's like a copying the raw format of data to do the changes. So now if you can just sorry if you can just delete the record. I will show you what is list. Now for example the same column I will choose and you will go here create new data. If you go with list this is how the this is how the list is stored. contains all ungrouped data list. So what exactly you want to group? I will select these three records and I will group these three records are group and okay that means I'm just grouping wherever it is Jan Jan 1st I'm grouping Jan 15th I'm grouping and again these two it's these three are the same dates. uh Jan first we have repeat it is repeated two times I just selected few records and I grouped them together they are coming under one category yes because I I didn't change the name if you want to change the name I will show you it's like any name you can any name you can give I'll delete it and I will show again you're just grouping the data for example this is the data what I'm choosing what we are doing now is the same analysis or data transformation, data processing, data cleaning which we did in the last call that was with power query. If you remember whatever we did yesterday, it was all with respect to power query where I copied the column. I replaced the value I renamed the column. So data cleaning part what I did yesterday it was completely with power query advanced version of powerbi I can say we have used that now what I'm telling you is the same operation I mean we can do the same operation in a different way so I I'm just starting from the beginning we imported the data I will remove this column Okay, I'll just import the data again from the beginning. I will remove this. I'm just starting it starting again. So I'm importing the CST file. Yesterday uh you know by the end we had a question that is how to do the data transformation especially with a date time data type as we can see the changes in the data type format here slash I mean dash backslash so we wanted to do the data transformation it was not possible with the power query d so what I'm doing not only one option we have we have so many options to concentrate on this data I will move to table view. Now you can see the table view of the data. For example, you want to copy paste this data. Ctrl Ctrl V. It's not possible for me to do that with table view of PowerBI. But with Power Query, you can do it. Not an issue. For me to copy paste the original data, what I will do, you can just come here to data group. Go with the new data group option. You just date uh group Just the second sorry treatment date sorry this is a text data now what I will do first select the column apply the changes whatever the changes you want to do apply on this I just want to convert this to a date date type change you are changing the date and see as soon as you select the data any column as soon as you select you can see the name of the column column and the date and the data type of the column towards your uh right left hand side top. So now we want to do the changes here. I will select the select the column where where I want to do the changes. I'm applying the changes. Now I'm converting that to a date. It is dash it is backlash. You want to make sure all the data type should be aligned. And this column you can clearly make out it should not be a text format. It is a calendar date. You want either date time or date. So now I want date. I'm going with the date. You can see the column data type is changing now to date. Again you don't want like 1 January 2023. So come here apply the changes. you want date, month, year or you want whichever format you want you can choose. I'm just going with this DD mm Y by Y and dash format. This is usually uh everywhere people use the same format. Now you can see the data This is how you will do changes related to your columns in PowerBI itself. Sometimes if it is not possible in power query directly you can do that in power. Hope until here everything is clear. So we did change I mean we changed here and you can automatically see now it got converted to a calendar icon. Okay. So this data iron. Okay. So now what we are trying to do now we have another option. So as soon as you select the column so you you can see here don't select count distinct if you go with count so sorry okay so this will let you know the count or the count or the don't summarize usually we summarize you want to see the actual this is uncatategorized the data unate come here you can do category here you can this is by default category options you have but nothing to worry about it and concentrating on this data group we are creating a group data by view or multiple grouping data set so how you want to show failed in progress sess I want to group the data that is failed and in progress together I'm choosing I'm creating a group out of it and a group named out group. So failed and in progress successful earlier I was creating new group or exclude other group. Okay. And you can see that wherever it is successful, you can see that other wherever it is in progress and wherever it is. If you integrity in the data, the number you get wherever it is in progress and progress. If you want to change this to giving or if you want to name it you can see only two categories or in this categories and you can create a new column out of it to understand or to read this groups. purpose of doing ahead and make use of that information all the option whatever with respect to this is this is also called data transformation or again data clean all these options you will value. If it is numerical data, you get this. Now here you need to select and go. You can do it that I can show you here. For example, patient name, patient here and patient. Okay. So the data patient name and your patient name and patient. This is the table format of data. How to view? If you want to click on this, so here you will be able to see this data. This is the table view. So here you want to see the patient name. Here we can apply a advanced fitting and you can the data based on how exactly customer name begin with it contains particular customer name or and operator or operator logical operator. you can add and you can filter the data as per the requirement and then you can view that data here. So we will be learning all this in the coming up uh you know topic. So multiple ways we have to do this analysis not just one way. So this is about uh how this is how uh we can do the data type changes that we change the data type which it was not possible yesterday for us to do because of certain data type issue. Hope this is clear. So we know what are the different data types we have. We have discussed uh all these topics yesterday as today and until here we completed like we also know how to create a column and how to do the data We will learn more about data transformation in the other examples also. See whenever we say data transformation it is also about sorting arranging in ascending to descending or grouping the data just what we did removing the duplicates. Thanks. do it in power query or powerbi it is almost the same power queries as it is already integrated within sorry powerbi changes or uh transformations what we are doing advanced transformation let us discuss today that is merge query append the query p column unpumn create calcul calcated columns create calculated tables. Apart from the basic transformation, we can also go with the advanced operation. What is this merge queries? Append queries. If you want to merge multiple columns together. So column- wise if you want to merge the data then we go with mer that is called as merge query. I will show you how to do manually. I will show you that to talk about append queries. If you want to append row wise like you have five rows I will give you another five rows. You append you append the data now it is 10 rows column wise three columns you have again add a new column to it that will be your six columns right now in just a second. So create calculated columns. If you want to do any calculation and if you want to store it in a new column that we are doing it here then create a calculated tables in a table wise also you can do the calculation p column unp excel how we do data p like how we use the p option what we have in excel we can also do that in p columns like based on column wise preparing the data or based on row wise preparing the data that is p and un keyboard what we have. I will show you all these examples now. So to demonstrate how to clean and transform sales data by creating I think this conditional logic is done. This is about merge query. Merge is all about see product ID sales amount you have in one one data in the other sheet of data you have another data. So you want to join them together. It is a type of query that combines a data from two or more tables. You have Excel sheet data, you have a CSV file data. You want to merge them together. That is possible with respect to PowerBI. We are merging two data sets. That means two tables we are merging together. With respect to append or merge. So we have different types. You can see the purpose, join type, join condition and the result. Combines data based on a common column. Add rows to the end of the table. Then you merge column will be merged together. When you go with append operation, rows will be added together. This you can expect as a interview question. So merge is to add multiple columns. Append is to add multiple rows. Whenever you go with merge query, you have options like inner, left outer, right outer, full outer or a cross joint. When you go with append, it is appending the rows, right? So all the columns by default will be added. So union or union all it is. When I talk about merge column, you can merge based on a particular column like a primary key or all columns if you want you can merge together. So in case of merge requires a common column for matching the rows. Here no column is required because you are merging below one below the other. New table with rows from both the tables based on the joiner. New table with rows from appended tables. Here you can see multiple columns and the rows will be added. There also you will see multiple rows will be added just under the same column. So append and merge are the two different operations which we will be doing. The main purpose of doing this is to merge different data sources together or merging different merging or appending different data sets together. Any questions here? We will I mean I will show you how to do all this but for now understand these topics. I will show you how to do it. Hope you all can see this PPT. So what I'm trying to do now is one is merge and the other one is append. When I talk about merge this is your data set one plus this is your data set two. You have three columns here you have three columns here you are merging. So the final result is nothing but six columns. This is the table only. The three column is also a table and the other one is also a table. But combines data based on the common column. You you will create a link from one table to another table and you can grab all of them together. It can be a inner join or it can be less outer join or sometimes even if you don't have a common column if you just want to merge them together it is possible to do that like adding new columns to the existing data source. How we added new rows and we saved it. When you refresh it, you get the new rows, right? That is nothing but append query where in this case here you have three rows. Append. This is the append query. Here you have four rows. Four rows. The final result will be three + 4 which will be seven rows. Here it goes row wise like rows will be getting appended. At the end the new records will be added. For example, yesterday's example like it was first five rows yesterday I added two or three records to it again like a row once the new records added that is called as the operation is called as append query. When I talk about merge merging the data set together that is based on the column. So the main purpose of doing all this adding, merging, adding rows, adding column, it is all to concentrate on the data basically the data set and the column names and also to have one proper data set or maybe like multiple data sets combined together to build the dashboard. For all this we will go and do all this operations, CAD, data quality, improve the performance and the business logic to create a relationship. So data in data modeling we come across this cardality to to check the connection between one data set to another data set. Maybe one data and then other data may have one to one connection or one column with multiple connections or many column many connections. So that we will see today that's the today's agenda actually that is data model. So data quality of course any data whether you merge or you append always maintain the data maintain the data and the data should be clean with a very good quality. Data consistency is very important. Improve performance optimize relationships by using appropriate data types and index. You already know how to do changes to the data type columns. business logic align the relationship with the underlying business logic and the data requirement because when you're merging columns or when you're adding new rows always we need to check whether at the end are we getting the right data result or not because it's not about having a big data but having a quality data and a data which is giving you endless information business logic it's important so let us work on this now so to demonstrate how to combine data from two different sources such as a CSV file with the movie ratings and a JSON file with the movie data using merge queries in PowerBI. So you can see uh whenever you import apart from Excel file or CSV file if you import it will directly take you to power query. The main reason is when the data is an excel file it clearly shows that we have worked on that data. So it will ask you to load the data. You can see as soon as you input you will get load or transform. When you when you select load option the data will be automatically loaded and you can see that in data pane. But when you select transform option it will automatically take you to power query. The reason behind it is you can do the data transformation you can do the data quality check. You can work on the data manually before going with the dashboard. That is the purpose of that is the difference between load and transform. This also you can expect like you know as an interview question what is the purpose of going with load what is that transform option what is the usage of it that's the usage like when the data is excel automatically it will ask you to load or you can also go with transform option so I imported the data and JSON file as it was the reason so it took you to I mean it take it will automatically take you towards power query but now you can close it and you can come back you can see the movie details here and you can also see the ratings here. If you go with this table view, you can see this. Right now it is movie details. If you move to ratings, you can see the ratings. Now let us move to data table or the model view I can say. So this is the model view. Model is nothing but to check the common uh details here between movie details. I mean check the common column. The common column here is movie ID and movie ID. It is one one to one connection. See I don't have rating here or I don't have a reviewer name here. I don't have a director or I don't have a title. Only column which is getting connected here is the movie ID. You can check in you can check the schema in the model view. You can see here the model view. I selected the model view. If you move towards table view you can see the tabular data structure of this. Now we are moving towards append query and merge query. Okay, for that we need to move towards power query directly. After importing the data you can move towards transform data. Hope you can see. Select the table that means selecting the movie details. Okay, we selected the all the column here. You can see the transform column option we are getting. So you can see here merge the columns or you can also see here uh remove the column remove other column add column remove duplicate remove error. You can you already know how to do all the changes but now we are going with the append and merge. So we have a common column that is movie ID and you can see here we have an option that is to add add as add as new query or you also have an option to group the data here. If I go ahead and check the title, you can see add as a new query. And here also you can see add as a new query. Bring down split the column. Splitting the splitting the column. I think I can discuss on that data. Come to the CSV file. Now here you can see add as a new query or other options whatever we have in transform also. You can see the same options whatever we have. See here add as a new way. So as a new data this column is particularly added here. So you can also just delete it here. Just a second. I'm just checking here the column. Okay. So movie ID, movie ID, uh title, rating. Okay. So now comes merge the query, append the query, merge queries as new. Always go with merge queries as new. I hope you all can see on top under option uh any column you can select that is not an issue. You will get this merge query and append queries every time. I will just come to merge query. What you want to merge? So this is the movie details column. I want to merge the ratings column. As you can see, I'll show again. I think I just did it without showing. First select I'm just selecting movie details. Come and select any of this column or all the columns also you can select. Not an issue. This is your this is called as tables or queries also it is called. Come to this merge query. So merge query means merging the columns. Okay. Select this merge query. This is your movie details based uh what you want to merge. Now come here. This is the current data. Movie details is already here. This table is already here. Go to the ratings column. Okay. So what joint you want to do? You want to go with left outer, right outer, full outer, inner joint, left ant, right? I will show you all that one by one. Use fuzzy matching to perform this much. This is automatically matching. That is nothing but the option. So I'm going first with left outer and no this. So here this is the data here this is one second I should get the ratings column. Here it is movie ID. Here also it is movie ID. You need to select the common column that is movie ID. Movie ID. It's the common column. See the selection matches three of three rows from the first table. Not in. Now you can see in movie details this data is added. You can just select it and you can go with expand. Okay. Now all the data is expanded based based on movie ID. You are merging all the data. The movie ID is one. Movie title is here. Just a second I will explain again what I did. So movie ID is here. Movie title is here. This is director. Now I just went to the CSV file and I grabbed movie ID, rating and reviewer name. So you can see movie ID, uh rating and the reviewer name. You can also see from which column we are getting it. What I did is if I just do this see this is nothing but after you merge it you will get this option. This is nothing but the table is added…

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