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Hi everyone! I’ve just published a new article on partitioning and incremental refresh in Power BI semantic models. 👉 Unlocking the Power of Partitioning in Power BI: The Game-Changer for Semantic Models! Check it out here:https://lnkd.in/d6Ujs6vy

You can improve refresh time and Power BI semantic model memory footprint with this one easy trick! Change the "Available In MDX" column property from "True" to "False". The only downside is the column can no longer be displayed in an Excel pivot table. That's it! Here's a view of Vertipaq Analyzer against some large dimension table key columns. The hierarchy size of just the 5 columns I'm showing is almost 300MB. That memory usage can be eliminated by changing the "Available In MDX" property of those columns. The refresh time will also be reduced slightly because the Vertipaq engine doesn't have to spend the time to generate the hierarchies. The impact may be doubled because the columns I'm showing are in dim tables, the same keys are also foreign keys in the fact table(s) so freeing up even more memory and saving even more refresh time. So how do you change the property. Just find the column in Tabular Editor, 2 or 3, and in the Options section of the column properties, find the "Available In MDX" option and switch it from "True" to "False". Again, the only tradeoff is whatever column is not available in MDX will not be able to be used in an Excel pivot table since it uses MDX to query the semantic model.

Exciting News! 🚀 Power BI now supports downloading large semantic models, enhancing data management capabilities! You can now download large semantic models as .pbix files directly from the Power BI service to Power BI Desktop, making it easier to work with complex data offline. Here's how to download: - Open the workspace content view in the Power BI service. - Find the semantic model you want to export and select More options (...). - Choose "Download this file" from the menu. If this option isn't shown, you're likely trying to download a .pbix in a scenario listed under Limitations. Remember, there are a few limitations to keep in mind: - You must be at least a Contributor to the workspace. - Semantic models with incremental refresh can't be downloaded to a .pbix file. - Models modified using the XMLA endpoint can't be downloaded. - Downloading is subject to size limitations, with a maximum data model size of 50 GB. - Models with automatic aggregations enabled can't be downloaded. - Models enabled for large semantic model storage format cannot be downloaded using REST APIs; use the Power BI Service instead. Embrace this new feature to streamline your data processes and optimize reporting workflows! #PowerBI #DataAnalytics #BusinessIntelligence #PowerBIUpdates #DataManagement #TechNews

Welcome to our in-depth demonstration of Datagaps' BI Validator! Ensure the validity and accuracy of your Power BI Reports, especially post-updates and upgrades. https://hubs.la/Q02KcB3G0 In this video, we tackle common challenges like visual element displacement, unintended KPI changes, and meta-report alterations. Watch our expert show how Datagaps' BI Validator turns these challenges into triumphs with efficient and comprehensive validation processes. ➡️DataOps Suite BI Validator: https://hubs.la/Q02KcBwB0 ➡️BI Validator – Try it FREE for 14 days: https://hubs.la/Q02KcFBP0 #PowerBI #DataValidation #BIValidator #Datagaps #DataIntegrity #BusinessIntelligence

-Sunday dosage: In Power BI, relationships are key to creating a concise data model. A relationship allows filters applied to a column in one table to automatically propagate to other related tables. This seamless flow of filters through relationship paths enhances data analysis by ensuring that insights are consistent across multiple tables, even when dealing with complex datasets. Harnessing the power of relationships in Power BI is essential for building dynamic, interconnected reports. #dataanalytics #powerbi #datascience #tablerelationship

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Are you ready to take your data presentation to the next level? Our video tutorial, "How to Configure Label Parameters in Bold BI," is here to guide you through the process! 🎥✨ 🔍 What You'll Learn: - Step-by-step instructions on configuring label parameters. - Tips to enhance the clarity and impact of your data visualizations. - Best practices for customizing your labels to fit your unique needs. 🔧 Why Watch? - Improve your data storytelling. - Make informed decisions with clearer insights. - Enhance the overall user experience of your BI dashboards. 📺 Watch Here: https://lnkd.in/eNuByzKr Don't miss out on this opportunity to refine your skills and make your data work harder for you! 💼📈 #BoldBI #DataVisualization #BusinessIntelligence #DataAnalytics #TechTutorial #ProfessionalDevelopment #DataDriven #VisualizationTips #BI #TechSkills 👉 Follow us for more tutorials and updates! 💡

Unlock the power of scalable data models in Power BI with composite models. Learn how to seamlessly integrate and manage large datasets. https://lnkd.in/gvxe_Ewi #microsoftpowerbiconsultant

Why Dual Mode is the Best Choice: DirectQuery: Data is queried live from the source, which is suitable for real-time needs, but performance could suffer for large datasets or aggregated views without any caching. Drawback: Performance hit when querying data repeatedly under RLS. Import Mode: Imports the data fully into Power BI, providing fast performance and flexibility for analysis. Drawback: It lacks dynamic querying of live data and might not suit scenarios where the underlying dataset is large and needs real-time updates. Live Connection: Directly connects to a live semantic model or data source without locally cached data. Drawback: It doesn't allow the creation of additional local tables or semantic modifications. Dual Mode: Combines the benefits of Import and DirectQuery, enabling specific tables to behave either way depending on the operation (e.g., summarized views vs. user-specific filtering). Advantage: Perfect for hybrid scenarios like this, where some users need filtered data (RLS for sales employees), and others require full data access. #PowerBI #DataModeling #Analytics #DAX #PowerPlatform

𝙃𝙤𝙬 𝙍𝙚𝙢𝙤𝙫𝙞𝙣𝙜 𝘾𝙤𝙡𝙪𝙢𝙣𝙨 𝙄𝙢𝙥𝙖𝙘𝙩𝙨 Model Size 𝙞𝙣 𝐈𝐦𝐩𝐨𝐫𝐭 𝐌𝐨𝐝𝐞: (𝐏𝐨𝐰𝐞𝐫 𝐁𝐈) 💻 𝐃𝐚𝐭𝐚 𝐒𝐭𝐨𝐫𝐚𝐠𝐞 -> In 𝐈𝐦𝐩𝐨𝐫𝐭 𝐌𝐨𝐝𝐞, Power BI compresses and stores the data from your source system into the 𝐏𝐨𝐰𝐞𝐫 𝐁𝐈 𝐦𝐨𝐝𝐞𝐥 (in-memory). -> Every column you import from the source consumes 𝐦𝐞𝐦𝐨𝐫𝐲, even if it’s not used in the report visuals, filters, or calculations. ✨ 𝐂𝐨𝐥𝐮𝐦𝐧 𝐂𝐨𝐦𝐩𝐫𝐞𝐬𝐬𝐢𝐨𝐧: Power BI uses a 𝐕𝐞𝐫𝐭𝐢𝐩𝐚𝐪 𝐞𝐧𝐠𝐢𝐧𝐞 that compresses data very efficiently, but columns with high cardinality (lots of unique values) take more space, and so do unused columns Even if a column is well-compressed, it still contributes to the overall memory footprint of the data model ➡️ 𝐈𝐦𝐩𝐚𝐜𝐭 𝐨𝐟 𝐑𝐞𝐦𝐨𝐯𝐢𝐧𝐠 𝐔𝐧𝐮𝐬𝐞𝐝 𝐂𝐨𝐥𝐮𝐦𝐧𝐬: When you remove unused columns, 𝐏𝐨𝐰𝐞𝐫 𝐁𝐈 no longer needs to allocate 𝐦𝐞𝐦𝐨𝐫𝐲 for that data, directly reducing the size of your model. 🔸 This can lead to 👇🏼 𝐒𝐦𝐚𝐥𝐥𝐞𝐫 𝐟𝐢𝐥𝐞 𝐬𝐢𝐳𝐞𝐬: The .pbix file will become smaller after removing unused columns ⚡ 𝐈𝐦𝐩𝐫𝐨𝐯𝐞𝐝 𝐩𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞: A leaner model can be processed faster, with quicker load times and more efficient query performance ⌚ 𝐋𝐨𝐰𝐞𝐫 𝐦𝐞𝐦𝐨𝐫𝐲 𝐜𝐨𝐧𝐬𝐮𝐦𝐩𝐭𝐢𝐨𝐧: Smaller models consume less RAM on Power BI Report Server or Power BI Service, improving performance and scalability ↗️ - Abdullah Tariq 🤗 #powerbi #importmode #optimization #analytics #vertipaq #PBI #memory #performance