From ADF Inventory to a Fabric Operating Model: A Practical Migration Playbook
Migrating from Azure Data Factory to Microsoft Fabric is not a one-for-one conversion. This practical playbook helps you assess existing workloads, choose the right Fabric pattern—Mirroring, Copy jobs, Pipelines, or Notebooks—and validate the move safely through metadata-driven design, reconciliation, and phased cutover.
Medallion to Magic — Manufacturing Intelligence Platform on Microsoft Fabric
Microsoft Fabric brings Data Engineers, Data Analysts, and Business Users onto a single platform. Data Engineers build the ingestion, Lakehouse, Warehouse, and dbt transformation layers that move raw factory data through the Bronze → Silver → Gold Medallion layers. Data Analysts design the DirectLake Semantic Model, author the DAX measure library, and build the Power BI reports that surface production readiness intelligence. Business Users (manufacturing operations, supply chain managers, and executives) consume those insights through Power BI, the Inventory Insights data agent, and M365 Copilot, asking questions in natural language without ever opening Fabric. Inspired by the Data Factory & Data Integration Community Challenge. I built and end-to-end analytical solution on Microsoft Fabric, integrating batch-exported operational data from four U.S. factories, transforming it through the Medallion pattern, and surfacing the results through Power BI and an AI data agent.Playing the Zork game in Fabric as a Fabric App
Whether you are a pro-coder or a software maker, the new Fabric Apps feature offers an easy and powerful way to vibe code custom software applications and host them within Fabric. Although Fabric is a very serious SaaS platform, I now have the tools to play the Zork game within Fabric! I just deployed the Fabric App Hello World template and asked GitHub Copilot to merge the Visual Zorker into the Fabric App. Then, I only had to deploy it again. All in five minutes tops. Let's check out how this is done.The Fabric Admin Trap: Scaling Your Cleanup
We’ve all been there. It’s Friday afternoon, and you’re looking at your Microsoft Fabric tenant. It’s cluttered with dozens of abandoned test workspaces, half-finished projects, and “oops, I forgot to delete this” environments. You open the portal. You click. You wait for the page to refresh. You click again. You feel the rage slowly building. As admins, we are supposed to be power users, but we often spend more time navigating UI menus than actually managing our data. I decided enough was enough and turned to the Microsoft Fabric CLI (fab) to take back control. But the path to automation wasn’t a straight line.
From Days to Minutes:Revolutionising Fabric Data Agent Creation and fine tuning using VScode Plugins
A Big Boost in Productivity Data engineering is changing fast. Earlier, setting up a Fabric Data Agent meant spending 30 to 60 minutes clicking through portals and doing repetitive manual work. With AgentForge, this has changed completely. AgentForge brings Fabric Data Agent setup into VS Code, using natural language powered by the Model Context Protocol (MCP). What once took nearly an hour can now be done in just 2 minutes for most agents. Even complex agents that work with large repositories are ready in about 4 minutes. This is not just a small improvement—it’s a major shift from manual clicks to AI-driven workflows that save time and reduce mistakes.Automating Microsoft Fabric Workspace Deployments Using Fabric CLI and Python
Learn how platform engineering teams can automate the provisioning of Microsoft Fabric workspaces using Fabric CLI and Python scripts to deploy lakehouses, connections, shortcuts, sparkpools, pipelines, semantic models and many other artifacts, and compute configurations with dependency‑aware ordering. Discover how a configuration‑driven command can simplify workspace setup by reducing manual overhead and improving deployment consistency across environments.
