👀 Have you ever written a DAX measure with CALCULATE() and thought — “this should work!” — only to see it break unexpectedly? Or maybe you tried CALCULATETABLE() and magically, everything worked.

Both functions seem to answer the same question:

“How do I modify the filter context?”

But they work very differently — and using the wrong one can lead to confusing totals, blank visuals, and filters behaving oddly.

Today, let’s demystify CALCULATE() and CALCULATETABLE(), when to use each, and why CALCULATETABLE() is often the safer bet in complex calculations.

When Power BI reports run slowly, the issue often lies not in the visuals, but in the data model itself. Focusing solely on DAX formulas isn’t enough to solve performance problems. In this post, I’ll share three powerful yet often overlooked techniques to optimize your data model and boost report performance.

Power BI continues to reshape the world of data analytics with its monthly updates. The May 2025 release brings groundbreaking improvements in user experience, modeling, and visualization. In this post, we’ll explore three powerful features that haven’t yet been deeply covered in the community blog—but are sure to make a big impact.

Microsoft is sunsetting Power BI Premium—mandatory migration to Fabric begins July 2024.

What you’ll learn:

✅Step-by-step migration guide (with automation scripts!)
⚠️Critical pitfalls to avoid (cross-region data = headache)
💡Pro tips to optimize costs in Fabric

Power BI's latest game-changer is here: TMDL (Tabular Model Definition Language) is revolutionizing how we handle data modeling. Imagine setting up your entire measure framework in seconds, viewing all your measures in a single screen, and automating your best practices right from the start. In our latest blog post, we dive deep into this powerful new feature that's bridging the gap between casual BI users and professional developers. Whether you're a Power BI veteran or just getting started, discover how TMDL can transform your workflow and save you countless hours of development time. Ready to supercharge your Power BI development? Read on to learn how TMDL is reshaping the future of data modeling.

Unlocking the Power of Direct Lake Mode: A Deep Dive into Microsoft Fabric's Game-Changing Feature

Want to handle billions of rows of data with lightning-fast queries? Microsoft Fabric's Direct Lake mode makes it possible, but only if you know how to harness its full potential. In this comprehensive guide, we reveal the critical optimization strategies that transform this powerful feature from a resource-hungry challenge into a streamlined data powerhouse. From sophisticated throttling mechanisms to advanced compression techniques, discover how to architect your data lake for peak performance while avoiding common pitfalls that can bottleneck your queries.

Learn the difference and what it takes to transition to Fabric successfully!

Unlocking the potential of Copilot

• Suggest content for a report
• Assisted Report Creation
• Prompt Data Insights
• DAX Formulation and Description

Hey there! Whether you're a seasoned pro or just dipping your toes into the world of data analytics, we all know there's a new player in town —Microsoft Fabric. Since the first Fabric Conference to the most recent updates, a lot of advanced capabilities have been introduced in the game. Let's take a moment to take a step back and brush up our Fabric basics, and ensure you are ready to revolutionize your data game.

The new Datamarts feature that was just announced in Microsoft build has a very special bonus for all the Mac developers that always wanted to work on Power BI Desktop but couldn't let go of their Mac..

In this video, I will walk you through how to easilyhttps://youtu.be/XZOPriif6Pw  create a custom PAGE NAVIGATION PANEL in Power BI with Bookmarks & Buttons. You will also learn many visualization tips and tricks along the way.

Did you ever have to combine a few tables, but you were not sure if you should do that in SQL Server with UNION ALL, in Power Query with APPEND or in DAX with UNION?

In general, where are the differences? And how do the three approaches behave in case of duplicate rows, unequal number of columns, deviating column names and order?

In this article we will analyze in detail the different approaches.

The post is relatively detailed, for all of those who consider it too long (tl;dr) here is the comparison table:

OLE DB or ODBC error while connecting to Amazon Athena from Power BI Desktop using ODBC connector

Dataflow Import API – How to deal with special characters?