Fabric Data Agent

Apr 27, 2026

Building a Fabric Data Agent with On‑Premises SQL Server Data

Many organizations still rely on on‑premises SQL Server for core operational workloads — finance, billing, ERP, manufacturing, and regulatory systems — that cannot be easily migrated to the cloud. At the same time, the business is demanding: Conversational access to data (“Ask the data” experiences) AI‑powered insights without building fragile ETL pipelines Faster time‑to‑value from analytics and AI Strong governance, security boundaries, and system ownership Microsoft Fabric addresses this challenge by allowing organizations to bring AI to their data before moving their data to AI. By leveraging SQL Server mirroring into Microsoft Fabric, organizations can continuously replicate on-premises data into OneLake, making it immediately available for analytics and AI—without disrupting source systems. On top of this foundation, semantic models and Fabric Data Agents enable governed, natural-language interactions powered by Microsoft Copilot.

Apr 25, 2026

The Agents: Data Agent & Operations Agent in Practice

A solutions architect's deep dive into the two agents powering Fabric IQ - Data Agents and Operations Agents. Covers the execution chain, governance model, billing math, configuration levers, and the combined architecture where one agent detects and the other explains over a shared Ontology.

Apr 16, 2026

The GINO Crisis: How Ambiguous Models Break Humans and LLMs — and the Case for Kimball 2.0

This article focuses on good database schema design. It highlights an emerging anti-pattern (GINO - "Gold in Name Only") whereby data engineering teams have "polished up" bronze data and moved it into Gold, with multi grain facts, normalised structures, outer joins etc, and left it to the Data Analyst to sort out. This is bad enough but it breaks when LLMs are brought in. The article then covers 6 straightforward techniques to simplify and optimise data models to increase success of NL2SQL platforms such as FDAs

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!

Apr 26, 2026

Fabric Data Agents Series (2/4): Why Your Data Model Breaks AI in Microsoft Fabric

👉 If your data model isn’t solid, your AI won’t be either. In Part 2 of our Microsoft Fabric Data Agents series, we focus on the foundation that makes or breaks AI: your semantic model and data design. This session shows how to build AI-ready data foundations so Fabric Data Agents can deliver accurate, consistent, and trustworthy results — not hallucinations or ambiguity. 🎯 What you’ll learn: ✔️ Why naming conventions and clear definitions are critical for AI reasoning ✔️ How explicit measures improve consistency and trust ✔️ The role of star schema design in scalable AI analytics ✔️ Common failure modes that break Data Agents ✔️ Practical Fabric-native fixes to improve grounding quality Most AI projects don’t fail because of AI — they fail because of bad data modeling. This session gives you the frameworks to fix that. 🚀 Whether you're a Power BI developer, data engineer, or architect, this is your blueprint for moving from experiments → production-ready AI systems. 👉 Watch Part 1 to understand Fabric Data Agents fundamentals 👉 Continue with Parts 3 & 4 to master architecture and governance at scale 👍 Subscribe for more deep dives on Microsoft Fabric, Power BI, and AI-driven data platforms #MicrosoftFabric #PowerBI #DataModeling #FabricDataAgents #AIinAnalytics

Apr 23, 2026

Microsoft Fabric: 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!

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.

May 20, 2026

Fabric Data Agent in a Day

Fabric Data Agent in a Day is a hands-on half-day workshop on Microsoft Fabric Data Agent, scheduled for 20 May 2026 in Milan, designed to show how to move from raw data ingestion to conversational agents that can answer business questions in natural language. During the session, participants populate a Lakehouse and a SQL Database in Fabric, build a first SQL-based Data Agent, make it more effective for Italian-language queries, apply Row Level Security, and measure its performance with Microsoft’s evaluation tools. The workshop then moves to a second agent built on a semantic model with DAX, so attendees can compare the semantic-model approach with the SQL-based one. Overall, the workshop is meant for data and BI professionals who want a practical introduction to building secure, multilingual, end-to-end conversational AI experiences on top of Microsoft Fabric data, using patterns that are closer to real projects than to simple demos.

May 7, 2026

Part 3 / 4: Fabric Data Agent Architecture Patterns: Choosing the Right Consumption Path

Part 3 or 4: Explore the most common and successful architectural patterns for consuming Fabric Data Agents: native Copilot experiences, custom business Q&A apps, agent-to-agent developer workflows via MCP, and enterprise data APIs with optional agent translation. Learn how to choose between Data Agent API, MCP server, and GraphQL depending on your consumers and risk profile.

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 Python SDK Notebooks

Notebooks to evaluate, automate, test data agents

Data Agent Workshop : FabCon EU 2025

Hands-on workshop material from FabCon Vienna 2025 on building 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 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

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.