Choosing the Right Way to Run Python in Microsoft Fabric
Fabric gives us several ways to run Python, and at first they can look overlapping. In this post, I share the practical decision model I use to choose the right option based on execution mode, compute engine, and data access path. If you are code-first and want fewer wrong turns when moving from exploration to production, this guide is for you.Understanding the Differences Between DAX UDF and Fabric UDF in Power BI and How to Use Them
This article examines the two types of User-Defined Functions (UDFs) supported in Power BI—DAX UDFs and Fabric UDFs. It outlines their key differences, typical use cases, creation approaches, and capabilities, offering practical guidance on how each can be used to enhance data modeling and enable deeper integration across Power BI and Microsoft Fabric environmentsUnderstanding UDF in Microsoft Fabric: Two Concepts, One Acronym
The Confusion Ends Here Working with Microsoft Fabric? Then it's only a matter of time before encountering the acronym "UDF"—and wondering what it really means. Is it a Power BI thing? Data Engineering? The answer is: it's both. The good news: once the distinction is clear, choosing the right UDF becomes intuitive. And more importantly, understanding both reveals how Fabric's workloads are designed to work together seamlessly. What Makes UDFs Worth Understanding Both User Defined Functions (in Power BI) and User Data Functions (in Data Engineering) embody the same software engineering principle: modularity and the DRY principle—Don't Repeat Yourself. Yet they solve completely different problems. Power BI's UDFs let analysts encode business logic once and reuse it across every dashboard and report. Data Engineering's UDFs enable data engineers to write transformations once and apply them wherever data needs to be processed. In both cases, the benefit is the same: one source of truth, no duplicated code, and centralized maintenance. It's the difference between building consistent analytical metrics and processing data at scale—and why organizations need both. Dive Deeper Curious about how to leverage both? Ready to architect Fabric solutions that follow software engineering best practices?Direct Lake: Faster Power BI, No Refreshes, Seamless Fabric Integration
OneLake is a unified storage system in Microsoft Fabric that eliminates data silos by storing all data in a single location. Now, we’re going to discuss Direct Lake, a new way Power BI interacts with this storage for faster performance and efficiency. Source: https://learn.microsoft.com/en-us/fabric/fundamentals/direct-lake-overviewMicrosoft Fabric Lakehouses: The Engine Room of Data Engineering
Microsoft Fabric revolutionizes data architecture by offering a unified platform that integrates Power BI, data science, real-time analytics, and more. At the heart of this ecosystem is the Lakehouse, a powerful, flexible, and scalable storage layer tailored for modern data engineering workflows. In this article, we explore how Lakehouses work in Microsoft Fabric, how to set one up, and how they serve as the foundation for managing both files and structured data—all without the traditional complexity of data platforms.
