📌Power BI Technical Questions asked in LTIMindtree 📌 Explain the concept of bi-directional cross-filtering in Power BI. What are its implications on performance and when should it be used or avoided? 0️⃣ Describe the process of implementing row-level security in Power BI. How does this change when using DirectQuery vs. Import mode? 1️⃣ How would you handle slowly changing dimensions in Power BI? Discuss both Type 1 and Type 2 SCDs? 2️⃣ Explain the differences between calculated columns and measures in DAX. Provide scenarios where you would use each? 3️⃣ How can you implement many-to-many relationships in Power BI? Discuss different approaches and their pros and cons? 4️⃣ Describe the EARLIER and EARLIEST functions in DAX. Provide examples of when you would use each? 5️⃣ How would you approach creating a dynamic TopN report in Power BI without using parameters? 6️⃣ Explain the concept of evaluation contexts in DAX (row context vs. filter context). How do these affect calculation results? 7️⃣ Discuss the differences between Import mode, DirectQuery mode, and Composite mode in Power BI. When would you choose each? Microsoft Fabric Questions: 8️⃣ What is Microsoft Fabric and how does it relate to Power BI? 9️⃣ Explain the concept of a lakehouse in Microsoft Fabric. How does it differ from traditional data warehouses? 1️⃣0️⃣ Describe the process of setting up a dataflow in Microsoft Fabric. How does this differ from Power BI dataflows? 1️⃣1️⃣ How can you use Spark in Microsoft Fabric for data processing? Provide an example scenario? 1️⃣2️⃣ Explain the concept of DirectLake in Microsoft Fabric. How does it impact Power BI report performance? Follow Saddam Hussain for more.... #SQL #Python #Excel #DataScience #Upskill #DataAnalyst #Powerbi #interview #DataAnalysis #Data #Excel #R #dataanalystjobs
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Hello Everyone, I have recently completed Power BI course on Codebasics and also completed a project that took me through various tools and techniques to transform data into insights. Here's a short glimpse of it. ▶𝐋𝐞𝐚𝐫𝐧𝐭 𝐓𝐞𝐜𝐡 𝐒𝐤𝐢𝐥𝐥𝐬 : ** 📊 Power BI Desktop** - Crafting interactive and insightful visuals. ** 📈 Power Query ** - Transforming and cleaning data effortlessly. ** Excel ** - Powerful and effective tool for analysis. ** Dax Language ** - Creating powerful calculations and measures. ** 📊 Dax Studio ** - Performance optimizer ** 👨🏫 Project Charter ** - Blueprint for a successful project. ▶𝐋𝐞𝐚𝐫𝐧𝐭 𝐁𝐈 𝐓𝐞𝐜𝐡𝐧𝐢𝐪𝐮𝐞𝐬 : ** Power BI ** - Calculated columns to dynamic titles and KPI indicators and new card visuals , DAX measures , conditional formatting of visuals . ** 🖥 Data Modelling ** - Building a relationship between the dimension tables and fact tables. ** 📑 Bookmarks & Page Navigation ** - Enhancing the user experience with interactive dashboards with exclusive popups. 📊. ** Data Table Creation ** - Vital step for time based analysis. ** Filters / Slicers ** - Useful for users to easily slice and dice the data. ** Data Validation ** - Ensuring data accuracy and reliability. ** 📊 Power BI Services ** - Making the insights deliverable/available in the cloud. ** ☁ Publishing ** - Sharing the reports through Power BI services. ** key Business Metrics ** - Gross margin to year to date performance. ▶𝐋𝐞𝐚𝐫𝐧𝐭 𝐁𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐑𝐞𝐥𝐚𝐭𝐞𝐝 𝐓𝐞𝐫𝐦𝐬: ** Net Profit ** Net Sales ** Gross Margin ** COGS ** Forecast Accuracy ** Net Absolute Error ** Year To Date ** Year To Go Check out the live dashboard link and let me know on your suggestions on the comment. Link :- https://lnkd.in/gvns4BX6 Had an amazing learning experience on Power BI. Thanks for creating such an amazing course Dhaval Patel and Hemanand Vadivel. Feel free to connect with me on discussion and explore the data analytics opportunities . #dataanalytics #sql #powerbi #datavisualizations #data #dataanalysis #datadrivendecisionmaking #businessinsights
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Data Transformation and Cleansing Mastery: Harnessing Power Query for Excel and Power BI Regardless of whether you're a dedicated Excel user or a Power Bi Developer , Power Query stands out as an essential asset capable of fundamentally altering how you manage data transformation and cleansing endeavors. Through intuitive actions, Power Query enables seamless extraction, alteration, and integration of data into a structured format optimized for analytical exploration. Bid farewell to arduous manual adjustments, as this tool streamlines the entirety of the procedure, granting you access to potent functionalities with minimal effort. #powerbi #microsoft #businessintelligence #excel #dataanalytics #datascience #data #tableau #datavisualization #sql #dashboard #office #analytics #python #business #dynamics #bi #software #bigdata #digitaltransformation #azure #dataanalysis #powerapps #machinelearning #technology #dashboards #microsoftpowerbi #o #cloud #businessanalytics
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Hey everyone, I'm thrilled to announce that I've finally finished the Codebasics Power BI course! 💯 At the end of the Codebasics Power BI course, Dhaval Patel assigns two tasks as part of the project. Task 1 Determine whether the customers in the 'Customer Performance' sales view meet the GM% target. Task 2 For the top 5 countries, identify the top 5 products and bottom 5 products based on GM% growth YoY and analyze the post-discounts % trend for each customer. 𝗟𝗲𝗮𝗿𝗻𝘁 𝗧𝗲𝗰𝗵 𝘀𝘁𝗮𝗰𝗸𝘀 ✔ Excel ✔ SQL ✔ PowerBi Desktop ✔ M language ✔ DAX language ✔ DAX studio (for optimizing the report) ✔ Project charter file 𝗟𝗲𝗮𝗿𝗻𝘁 𝗣𝗼𝘄𝗲𝗿𝗕𝗜 𝘁𝗲𝗰𝗵𝗻𝗶𝗾𝘂𝗲𝘀 ✔ Creating calculated columns ✔ Creating measures using the DAX language ✔ Data modelling ✔ Using Bookmarks to switch between two visuals ✔ Page navigation with buttons ✔ Creating date table using m language ✔ Dynamic titles based on the applied filters ✔ Using KPI indicators ✔ Conditional formatting of the values in visuals ✔ Data validation techniques ✔ PowerBi services ✔ Publishing reports to PowerBi services ✔ Setting up the personal gateway to set up the auto-refresh of data 𝐁𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐫𝐞𝐥𝐚𝐭𝐞𝐝 𝐭𝐞𝐫𝐦𝐬 ✔ Gross price ✔ Pre-invoice deductions ✔ Post-Invoice deductions ✔ Net Invoice sale ✔ Gross Margin ✔ Net sales ✔ Net profit ✔ COGC - the cost of goods sold ✔ YTD - Year to Date ✔ YTG - Year to Go Thanks to Dhaval Patel and Hemanand Vadivel for creating such an intuitive course. 💯 I had an amazing experience learning Power BI. Whether you're from a technical or non-technical background, this course is the best. If you're interested in learning Power BI, head over to the website. https://lnkd.in/gAUXFZRq Check out the full interactive dashboard at the link below, and feel free to share your suggestions in the comments section.⬇ https://lnkd.in/gPNf9svj GitHub link https://lnkd.in/gGJdKKNU #powerbi #microsoft #dataenthusiast #dax #datacleaning #datamodeling #dataanalysis #datascientist #dataengineer #businessintelligence #mysql #excel #powerbideveloper #google #microsoft #meta #amazon #bigdata
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I wish I knew this in my early Power BI days! These tips would've saved me so much time and effort. If you are just starting out, keep these in mind: 💡 Improve Query Performance with Query Folding Instead of letting Power BI process everything, query folding lets you push the work back to the data source (like SQL Server). This makes your reports load much faster, especially with large datasets. You can check if it's enabled by right-clicking a query step in Power Query and selecting "View Native Query." 💡 Use Composite Models for More Flexibility Composite models let you combine real-time data (DirectQuery) and imported data in a single report. This means you can get up-to-date insights while still keeping your reports fast and efficient. 💡 Create Custom Visuals with R or Python When the built-in visuals aren't enough, Power BI lets you use R or Python to build custom visuals. It’s perfect for creating more complex charts and analysis. 💡 Simplify DAX with Variables DAX variables allow you to store intermediate results within your formulas, making your calculations cleaner and easier to understand. They also help boost performance by avoiding the need to repeat the same calculations multiple times. 💡 Control Data Access with Row-Level Security (RLS) Row-Level Security (RLS) ensures users only see the data they need. For example, a regional manager would only have access to their region’s data, keeping everything secure and relevant. 💡 Create Interactive Reports with Bookmarks & Selections Bookmarks capture specific views of your report, and selections control which visuals appear. Together, they make your reports interactive and easy to navigate—no need for multiple pages! 💡 Automate Tasks with Power Automate Power Automate lets you automate tasks like sending reports or triggering alerts based on changes in your data. It’s a huge time-saver and ensures everyone stays in the loop without manual effort. ~ If you're already using some of these, great! But if not, give them a try—they can make a big difference! ♻️ Repost to help others! PS: Credits to Raj Maradiya for sharing this amazing Power BI Desktop Cheat Sheet. ➡️ Download it here - https://lnkd.in/gkPQmswf #Cheatsheet #PowerBIDesktop #PowerBI #DAX #BusinessIntelligence
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cheat sheet
I wish I knew this in my early Power BI days! These tips would've saved me so much time and effort. If you are just starting out, keep these in mind: 💡 Improve Query Performance with Query Folding Instead of letting Power BI process everything, query folding lets you push the work back to the data source (like SQL Server). This makes your reports load much faster, especially with large datasets. You can check if it's enabled by right-clicking a query step in Power Query and selecting "View Native Query." 💡 Use Composite Models for More Flexibility Composite models let you combine real-time data (DirectQuery) and imported data in a single report. This means you can get up-to-date insights while still keeping your reports fast and efficient. 💡 Create Custom Visuals with R or Python When the built-in visuals aren't enough, Power BI lets you use R or Python to build custom visuals. It’s perfect for creating more complex charts and analysis. 💡 Simplify DAX with Variables DAX variables allow you to store intermediate results within your formulas, making your calculations cleaner and easier to understand. They also help boost performance by avoiding the need to repeat the same calculations multiple times. 💡 Control Data Access with Row-Level Security (RLS) Row-Level Security (RLS) ensures users only see the data they need. For example, a regional manager would only have access to their region’s data, keeping everything secure and relevant. 💡 Create Interactive Reports with Bookmarks & Selections Bookmarks capture specific views of your report, and selections control which visuals appear. Together, they make your reports interactive and easy to navigate—no need for multiple pages! 💡 Automate Tasks with Power Automate Power Automate lets you automate tasks like sending reports or triggering alerts based on changes in your data. It’s a huge time-saver and ensures everyone stays in the loop without manual effort. ~ If you're already using some of these, great! But if not, give them a try—they can make a big difference! ♻️ Repost to help others! PS: Credits to Raj Maradiya for sharing this amazing Power BI Desktop Cheat Sheet. ➡️ Download it here - https://lnkd.in/gkPQmswf #Cheatsheet #PowerBIDesktop #PowerBI #DAX #BusinessIntelligence
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Power BI Roadmap for Data Analytics! 🚀 Whether you're just starting out or looking to enhance your skills, this guide will take you through the essential steps to master Power BI and change your data into impactful insights. 1️⃣ Learn Basics: Start by understanding the main ideas of Power BI, like how to load data, make models, and create visuals. 2️⃣ Importing Data: Figure out how to bring in data from different places, like Excel, databases, or online services. 3️⃣ Transforming Data: Use the Power Query Editor to clean up and change your data so it’s ready to use. 4️⃣ Data Modeling: Get good at making a strong structure for your data, including connecting different tables. 5️⃣ DAX (Data Analysis Expressions): Learn DAX to do more advanced things with your data, like making new columns and calculations. 6️⃣ Create Visuals: Practice making good charts and visuals that show your data in a clear way. 7️⃣ Use Power BI Service: Learn about the online Power BI Service to share and work on reports with others. 8️⃣ Stay Updated: Keep an eye out for new things Power BI can do by staying updated with the latest features. 9️⃣ Practice: Practice using Power BI on real projects to get better at it. The more you use it, the more you’ll understand. #datascience #dataanalytics #Datascientist #python #programming #microsoft #DataAnalyst #BusinessAnalyst #PowerBI #DataAnalytics #powerbiroadmap #dataanalysis #dataanalyticscourse #super30dataanalyticsprogram #artofproblemsolving #venturebydatascienceexperts #analyticsshiksha #datarevolution #data #powerbiindataanalytics #powerbijobs #powerbiinterview #powerbitips
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Power BI desktop chart sheet
I wish I knew this in my early Power BI days! These tips would've saved me so much time and effort. If you are just starting out, keep these in mind: 💡 Improve Query Performance with Query Folding Instead of letting Power BI process everything, query folding lets you push the work back to the data source (like SQL Server). This makes your reports load much faster, especially with large datasets. You can check if it's enabled by right-clicking a query step in Power Query and selecting "View Native Query." 💡 Use Composite Models for More Flexibility Composite models let you combine real-time data (DirectQuery) and imported data in a single report. This means you can get up-to-date insights while still keeping your reports fast and efficient. 💡 Create Custom Visuals with R or Python When the built-in visuals aren't enough, Power BI lets you use R or Python to build custom visuals. It’s perfect for creating more complex charts and analysis. 💡 Simplify DAX with Variables DAX variables allow you to store intermediate results within your formulas, making your calculations cleaner and easier to understand. They also help boost performance by avoiding the need to repeat the same calculations multiple times. 💡 Control Data Access with Row-Level Security (RLS) Row-Level Security (RLS) ensures users only see the data they need. For example, a regional manager would only have access to their region’s data, keeping everything secure and relevant. 💡 Create Interactive Reports with Bookmarks & Selections Bookmarks capture specific views of your report, and selections control which visuals appear. Together, they make your reports interactive and easy to navigate—no need for multiple pages! 💡 Automate Tasks with Power Automate Power Automate lets you automate tasks like sending reports or triggering alerts based on changes in your data. It’s a huge time-saver and ensures everyone stays in the loop without manual effort. ~ If you're already using some of these, great! But if not, give them a try—they can make a big difference! ♻️ Repost to help others! PS: Credits to Raj Maradiya for sharing this amazing Power BI Desktop Cheat Sheet. ➡️ Download it here - https://lnkd.in/gkPQmswf #Cheatsheet #PowerBIDesktop #PowerBI #DAX #BusinessIntelligence
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How can you handle large datasets in POWER BI Desktop? To handle large datasets in Power BI Desktop efficiently, consider the following strategies: Incremental Refresh: Refresh only new or changed data to reduce load times. Data Reduction: Load only necessary columns and rows and aggregate data when possible. Query Folding: Push transformations to the data source to minimize processing in Power BI. Star Schema Modeling: Use a star schema with single-directional relationships to optimize performance. Optimize Data Types: Use efficient data types and avoid unnecessary calculated columns. Composite Models: Combine DirectQuery and Import modes to balance performance and real-time data access. DirectQuery Mode: Query large datasets in real-time without importing them. Data Compression: Utilize Power BI’s data compression features and avoid high-cardinality columns. Efficient DAX Calculations: Use variables and measures instead of complex calculated columns. Pre-Aggregation: Aggregate data at the source before importing to reduce dataset size. Simplify Visuals: Limit the number and complexity of visuals on a page. Parameterized Queries: Use parameters to control data load dynamically. Optimize Refresh Schedule: Set refresh times during off-peak hours and use incremental refresh for large datasets. These strategies help manage performance and resource usage effectively when working with large datasets in Power BI. #msfabrics #powerautomate #powerbitraining #powerapps #powerbi #businessintelligence #powerBIapps #powerbideveloper #powerbifreelancer #freelance #powerplatform #powerbijobs #powerautomate #office365 #azure #python #machinelearning #work #dataengineering #email #projects #mentoring #leader #sql #r #shiny #pipeline #excel #fabrics #hyperautomation
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Hi Everyone, I'm elated to share that I have finally completed Codebasics Power BI course. 💯 𝗟𝗲𝗮𝗿𝗻𝘁 𝗧𝗲𝗰𝗵 𝘀𝘁𝗮𝗰𝗸𝘀 ➡ SQL ➡ PowerBi Desktop ➡ Excel ➡ DAX language ➡ DAX studio (for optimizing the report) ➡ Project charter file 𝗟𝗲𝗮𝗿𝗻𝘁 𝗣𝗼𝘄𝗲𝗿𝗕𝗜 𝘁𝗲𝗰𝗵𝗻𝗶𝗾𝘂𝗲𝘀 ➡ Creating calculated columns ➡ Creating measures using the DAX language ➡ Data modeling ➡ Using Bookmarks to switch between two visuals ➡ Page navigation with buttons ➡ Creating date table using m language ➡ Dynamic titles based on the applied filters ➡ Using KPI indicators ➡ Conditional formatting of the values in visuals ➡ Data validation techniques ➡ PowerBi services ➡ Publishing reports to PowerBi services ➡ Setting up the personal gateway to set up the auto-refresh of data 𝐁𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐫𝐞𝐥𝐚𝐭𝐞𝐝 𝐭𝐞𝐫𝐦𝐬 ➡ Gross price ➡ Pre-invoice deductions ➡ Post-Invoice deductions ➡ Net Invoice sale ➡ Gross Margin ➡ Net sales ➡ Net profit ➡ COGC - the cost of goods sold ➡ YTD - Year to Date ➡ YTG - Year to Go Check out the complete interactive dashboard on the link below and let me know your suggestions in the comment section⬇ https://lnkd.in/gkXNjj6A I had an amazing experience learning Power BI, no matter if you are coming from a technical or non-technical background it's the best. Anyone who is willing to learn Power BI, head over to the website https://lnkd.in/dBD638za Special thanks to Dhaval Patel and Hemanand Vadivel sir for making such an intuitive course.💯 🙏 #powerbi #codebasics #dataanalysis #data #powerbitraining #dashboarddesign #dataanalytics #learninganddevelopment #project #datavisualization #sql #mysql #datacleaning #dax #datawrangling #datavalidation #businessanalyst #dataanalyst #datamodeling #businessinsights #powerbideveloper #bianalyst #DataAnalyst #RemoteWork #WorkFromAnywhere #TechJobs #CareerOpportunity #EntryLevelJobs #JobSearch #AnalyticsJobs
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I started my data visualization journey with Tableau but the gaining popularity of Power BI gave me the feeling of FOMO. So I started learning Power BI 3 months back and learnt about Power BI architecture, power query and bit of power automate But learning is never complete without a project so worked on my first end to end dashboard Tools used : 📊 Power BI: For building interactive visualizations and real-time insights 🧹 Power Query: For data cleaning, transformation, and handling complex data manipulations 🧮 DAX (Data Analysis Expressions): To create calculated measures and custom columns ⚙️ Power Automate: For automating email attachments from outlook to google drive 🔄 Power BI Service: To publish the dashboard and to setup automated data refresh Dashboard link: https://lnkd.in/dcDRpmv9 Which one do you prefer ? Tableau or Power BI ? Reply in the comments #powerbi #datavisualisation #dataanalytics #powerautomate #powerquery
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