Tired of Hacking DAX Just to Make a Chart Look Right? Fabric Apps Let You Build the Exact Dashboard
Ever needed a dashboard that looks a very specific way- a big trend number with a mini sparkline, a real-time ticking counter, a layout Power BI's report canvas just won't give you- and ended up stuffing extra measures and workarounds into your semantic model just to fake it? Fabric Apps let you build that exact look as a small custom web app that plugs into your existing model, and an AI coding agent can build most of it for you. Here's what it actually is, in plain terms, with one simple example.Fabric SDD+AI Series (2/3) | From Planning to Practice: How Data Contracts Guide Your AI [PT/EN/ES]
🇧🇷PT: Da teoria à prática: descubra como o Data Contract garante que sua IA no Microsoft Fabric trabalhe com dados limpos e precisos. Aprenda a guiar o GitHub Copilot para construir um Lakehouse blindado contra erros. 🇺🇸EN: From theory to practice: discover how the Data Contract ensures your AI in Microsoft Fabric works with clean and precise data. Learn how to guide GitHub Copilot to build a Lakehouse shielded against errors. 🇪🇸ES: De la teoría a la práctica: descubra cómo el Data Contract garantiza que su IA en Microsoft Fabric trabaje con datos limpios y precisos. Aprenda a guiar a GitHub Copilot para construir un Lakehouse blindado contra errores.Overcoming Common Challenges in Microsoft Fabric: A Practical Guide
Facing issues with data integration, performance, or governance in Microsoft Fabric? This guide breaks down the most common challenges and offers practical, real-world solutions to help you get the most out of your Fabric environment.
From 48-Hour Delays to 3-Hour Refresh Cycles: Modernizing Asset Intelligence with Microsoft Fabric
In large restaurant chains, keeping tabs on thousands of assets equipment, inventory, purchase orders, and transfers across hundreds of locations is a significant operational challenge. When that data lives in disconnected systems, gets reported manually, and arrives 24–48 hours late, the business is always flying behind the windshield. This post walks through how we helped Restaurant Industry Company replace a fragile, manual reporting pipeline with a fully automated Microsoft Fabric Medallion Lakehouse architecture , reducing data latency from 48 hours to under 3, eliminating manual reporting effort, and laying the foundation for AI driven forecasting.Programmatically Refresh & Sync SQL Analytics Endpoint Metadata in Microsoft Fabric
tl;dr The Fabric Lakehouse has a SQL Analytics Endpoint (SAE) that lets you query your data with SQL. It reads from your Lakehouse Delta tables, which live as Parquet files plus Delta logs. SAE sits on top of that storage, uses the metadata, and exposes a SQL friendly layer. That layer can lag a bit behind the Lakehouse, so you may want an extra sync step to keep data ready for Power BI, for example. For that, you can call the Fabric REST API’s Refresh SQL Endpoint Metadata operation. Disclaimer: This article talks about the Microsoft Fabric Lakehouse item and its SQL Analytics Endpoint. I also don't use built-in lakehouse sql analytics endpoint's semantic model from in this case.GraphQL Explained: Transforming Data Access in Microsoft Fabric
I recently got a chance to explore GraphQL, it was an absolute revelation. I realized I could finally have a more elegant way to expose the clean, curated data from our new Microsoft Fabric environment to modern applications. This blog post is a summary of that journey, explaining exactly what GraphQL is, why you need it, and how it transforms data access.
