Fabric Data Agent

Aug 16, 2026

Fabric Data Agent vs Copilot in Power BI

I get asked the same question in almost every Fabric estate review I run. Do we put Copilot on the semantic model, or point a data agent at the warehouse? It nearly always arrives as an intelligence contest, which one is smarter. That is the wrong question. In a Fabric estate where both ultimately work from the same governed gold data, the important difference is not the underlying data. It is how much semantic context sits between the question and that data, and the surface whose grounding matches the shape of the question is the one that answers accurately. The decision is architectural, not a bake-off. You have a clean setup: star schemas in gold, semantic models on top, reports that people trust. Now the business wants to type a question and get an answer. The reporting side says put Copilot on the semantic model. The warehouse side says point a data agent at the warehouse. Both are correct, for different questions and the failure mode is choosing on vibes.

Aug 4, 2026

Why the Retirement of Fabric Data Agent Integration in Copilot in Power BI Is a Strategic Shift, Not a Step Back

Microsoft Fabric continues to evolve rapidly as the unified data platform for the AI era. One recent update that data leaders, architects, Power BI practitioners, and partners should pay close attention to is the upcoming retirement of the Fabric data agent integration in Copilot in Power BI. According to public updates, the integration between Fabric data agents and Copilot in Power BI is expected to retire on August 26, 2026. Importantly, this does not mean Fabric data agents are going away. Instead, it reflects a strategic shift in how conversational analytics and agentic data experiences are being surfaced across the Microsoft ecosystem. Retirement of Fabric data agent integration in Copilot in Power BI

Jul 23, 2026

E-commerce ontology and data agent in Microsoft Fabric IQ

Your data can be clean, complete, and connected, and still fail to answer a simple business question. Microsoft Fabric IQ solves this with something called an ontology. I built one end to end, connected a data agent to it, and wrote down every step. If you have never touched an ontology before, this guide is for you. Without an ontology, an AI agent can only guess at your data.

May 29, 2026

Microsoft Fabric Data Agents LIVE Demo 🚀 | Real AI Use Cases Explained #vfpug

👉 Getting insights from your data shouldn’t feel like solving a puzzle. In this session, Jennifer demonstrates several Microsoft Fabric Data Agents in action, showcasing how conversational AI experiences can transform the way users interact with governed data. This session focuses on practical, real-world examples of how Fabric Data Agents enable users to ask questions naturally and receive grounded, trustworthy answers powered by Microsoft Fabric. 🎯 What you’ll learn: ✔️ How Fabric Data Agents work in real scenarios ✔️ Conversational access to governed enterprise data ✔️ AI-powered self-service analytics patterns ✔️ Practical Power BI and Microsoft Fabric integrations ✔️ Real-world approaches for delivering trusted AI experiences Whether you're a Power BI developer, Fabric practitioner, analyst, or architect, this session helps bridge the gap between AI concepts and real business value. 🚀 No AI background required — just curiosity about the future of data experiences.

May 26, 2026

Building NFL Analytics with Fabric, Power BI, and AI Agents

Video walkthrough building an end-to-end NFL analytics reference architecture in Microsoft Fabric using NFLVerse data, with accompanying GitHub repo. The video steps through the full pipeline (Bronze → Gold → semantic model) and compares two Fabric Data Agent patterns—Lakehouse (SQL) vs Semantic Model (DAX). We wrap by testing in Microsoft 365 Copilot and running agent evaluations to show how to iteratively improve natural language analytics quality.

May 26, 2026

How to use Data Agent Example Queries

Example Queries are THE key value differentiator between Microsoft Fabric Data Agents and all other RAG agents you can build, so let's dive into this topic with Bradley Ball, aka ‪@SQLBalls‬ , and look and how we can use them!

Aug 4, 2026

Get You #MicrosoftFabric Data Agent Tuned

The Beyond the Prompt: Tuning Microsoft Fabric Data Agents for Flawless Results is presented by Thimantha Vidanagamage and hosted by Adriano da Silva at the Microsoft Data and AI South Florida user group. 🎯 This presentation provides you with a blueprint on how to implement Microsoft Fabric Data Agents by covering the key concepts, best practices, and providing practical examples. 💡 Register Right Now to learn more about it. 💡 We will show you how to make this a reality at the Microsoft Data and AI South Florida User Group (DataAISF). - ABSTRACT: As organizations race to deploy AI Agents, it quickly becomes clear that standard prompt engineering isn't enough. To achieve production-grade accuracy, you have to go beyond the prompt and fundamentally change how you feed your data layers to the AI. 📌 TOPICS COVERED: * Microsoft Fabric Data Agents * Ontology * Embedding Semantic Metadata * and much more In Microsoft Fabric, your choice of data artifact directly dictates your agent's reasoning style and native language. In this session, we will deep-dive into how Fabric Data Agents interact with four distinct data paradigms: Semantic Models, Ontology, Data Warehouses, and Lakehouses. You will walk away with an actionable blueprint showing you exactly how to write context rules, embed semantic metadata, and supply technical query examples to ensure your Fabric Data Agents deliver flawless, trusted results every time.

Jun 25, 2026

Fabric Data Agents

Fabric data agents are now generally available in Microsoft Fabric, and they give teams a way to build conversational Q&A experiences over data sources like Power BI semantic models. But the real work is not just creating the agent. It is shaping the semantic model, instructions, examples, and feedback loop so the answers are robust. Which is why our next Wellington Power BI & Fabric User Group session is on Fabric data agents: what they are, where they fit, and how to get better results from them.

Jun 15, 2026

Microsoft Fabric Community Conference 2026

The annual Microsoft Fabric Community Conference featuring sessions on data agents, real-time analytics, and the latest Fabric innovations.

Agentic App with Fabric (incl Data Agents)

Agentic Banking App is an interactive web application designed to simulate a modern banking dashboard. Its primary purpose is to serve as an educational tool, demonstrating: How SQL-based databases are leveraged across different types of workloads: OLTP, OLAP, AI workloads. How agile AI-driven analysis and insight discovery can be enabled via prescriptive data models in Fabric. How easy it is possible to integrate other Fabric workloads (e.g., Report, Data Agent, Notebook) leveraging that data model. Through a hands-on interface, users can see the practical difference between writing a new transaction to the database, running complex analytical queries on historical data, and using natural language to ask an agent to query the database for them.

Data Agent Governance and Security Accelerator Using Purview

Enable Microsoft Purview Data Security Posture Management (DSPM) for AI across Microsoft 365 Copilot, Microsoft Foundry, Microsoft Fabric, and custom AI solutions with a spec-driven deployment and governance workflow.

Data Agent Python SDK Notebooks

Notebooks to evaluate, automate, test data agents

Data Agent Automation Using Python SDK

Notebook to automate creation, testing and updating data agent using Python SDK in Fabric notebook.

Data Agent External Client Python

A standalone Python client for calling Microsoft Fabric Data Agents from outside of the Fabric environment using interactive browser authentication. ⚠️This is in Preview and API can change until GA.

Data Agent Client - Teams App

A Microsoft Teams application that enables natural language queries to Fabric Data Agents, featuring real-time streaming responses, DAX query visualization, and multi-agent support. - Natural Language Queries: Ask questions in plain language and get AI-powered answers from your semantic models - Multi-Agent Support: Connect to multiple Fabric Data Agents and switch between them seamlessly - Real-Time Streaming: See responses as they're generated with live progress indicators - Query Transparency: View the generated DAX code and query results for each analysis step - Teams Integration: Native Teams app experience with SSO authentication - Fluent UI Design: Modern, responsive interface following Microsoft design guidelines