Welcome to the September 2024 Update! Announcements We have a lot of exciting announcements to share with you for FabCon Europe! We’ve brought Copilot to Dataflows Gen2 and a richer Copilot experience when building and consuming Power BI Reports. With Real-Time Intelligence we have redesigned and enhanced user experience in the Real-Time hub.
As you may have seen, AI Skill in Microsoft Fabric is publicly available, offering exciting new possibilities for users to create customized, data-driven generative AI experts within Microsoft Fabric. This post will demonstrate how you can extend the capabilities of Fabric AI Skill in Microsoft Fabric notebooks to deliver richer and more comprehensive responses using … Continue reading “Harness Microsoft Fabric AI Skill to Unlock Context-Rich Insights from Your Data”
Welcome to the August 2024 Update. Here are a few, select highlights of the many we have for Fabric. V-Order behavior of Fabric Warehouses allows you to manage the V-Order behavior at the warehouse level. Monitor ML Experiments from the Monitor Hub allows you to integrate experiment items into Monitoring Hub with this new feature. … Continue reading “Microsoft Fabric August 2024 Update”
Problem Statement In the previous blog on Profiling Microsoft Fabric Spark Notebooks with Sparklens, we covered how to run Sparklens to profile and tune the performance of your spark notebooks in Microsoft Fabric. In that blog, we used a custom Sparklens JAR. The Sparklens JARs available in the Maven Central repo supports only the Spark … Continue reading “Building a Custom Sparklens JAR for Microsoft Fabric”
We are excited to share guidance for how you can use Microsoft Fabric to turn your data into knowledge for Generative AI applications. This guide will walk you through implementing a RAG (Retrieval Augmented Generation) system in Microsoft Fabric using Azure OpenAI and Azure AI Search. By the end, you’ll be more familiar with how to … Continue reading “Building Custom AI Applications with Microsoft Fabric: Implementing Retrieval Augmented Generation for Enhanced Language Models”
