Tried using Lookup activity to read a file from Lakehouse in Microsoft Fabric?
Why Fabric Lookup Activity Cannot Read Lakehouse Files (And How to Fix It)
Views vs Shortcuts in Microsoft Fabric: Same Data, Different Stories
In Microsoft Fabric architecture, should I use a View or a Shortcut?
Optimizing Microsoft Fabric: Performance Solutions
If you’re working with Microsoft Fabric, this might save you some time.
Microsoft Fabric: Complete Guide + Common Errors and How to Fix Them (Real Production Issues)
Microsoft Fabric is a powerful platform that brings together data engineering, pipelines, lakehouse, and Power BI into a single ecosystem. However, once you move from demos to real production workloads, things start to break.
How to Refresh Power BI Reports from Azure Data Factory (ADF)
Automating your Power BI dataset refresh can save time and ensure your reports always stay up to date. In this post, we’ll walk through how to trigger a Power BI report refresh directly from Azure Data Factory (ADF) using an App Registration in Azure Entra ID.
How Azure Data Factory Changed the Way We Handle ETL/ELT at Scale
There was a time when moving data from multiple sources felt like untangling a giant knot. Every data refresh meant scripts breaking, manual checks, and long hours spent ensuring everything flowed from source to destination correctly. Then Azure Data Factory (ADF) entered the picture, and it didn’t just simplify ETL and ELT. It completely transformed how we think about data orchestration at scale.
Use Azure AI Services in Containers
Did you know you can run Azure AI services on your own infrastructure using containers? Microsoft provides container images for individual AI service APIs through the Microsoft Container Registry (MCR). This allows you to deploy AI closer to your data on-premises, in Azure, or even at the edge.
What to Consider Before Using Azure AI Foundry
Azure AI Foundry is a powerful platform for developing and scaling AI solutions. It gives teams structure through hubs and projects, shared resources, and collaborative tools. But to get the most from Foundry, it is important to plan carefully. From resource organization to cost management, a little forethought can make your AI journey smoother and more efficient.
Projects in Azure AI Foundry: Where Ideas Turn Into AI Solutions
A project in Azure AI Foundry is a workspace designed for a specific AI development effort. Each project connects to a hub, giving it access to shared resources while also providing its own dedicated environment for collaboration and experimentation.
Unlocking the Power of Azure AI Foundry
Azure AI Foundry is Microsoft’s dedicated platform for building, managing, and scaling AI solutions in the cloud. It is not just a collection of services, it is a structured environment designed to make AI development more efficient, organized, and secure.
Building Smarter with Azure AI Services
With Azure AI services, you don’t need to start from scratch. Microsoft provides a suite of prebuilt, ready-to-use APIs that let you plug AI into your apps and workflows right away. Here are some of the most powerful services you can use today:
Exploring the Core Capabilities of Artificial Intelligence
Today, the real magic of AI lies in its capabilities. These are the practical functions that bring intelligence into software applications. Let’s explore the key AI capabilities that developers are using to build smarter, more responsive, and human-like systems.
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