Fabric Data Agent

Apr 2, 2026

Programmatically Retrieve Prep Data For AI Configuration of Semantic Models

For Power BI Copilot and Data agents with semantic models, you must use Prep Data for AI configuration to ground the responses in the context added in Prep for AI. In this blog, I will show you how you can use the Power BI remote MCP server to get the configuration.

Mar 26, 2026

Fabric Data Agents: The Shift from Querying Data to Reasoning Over Knowledge

What’s the big deal? Fabric is no longer just a data platform. It’s becoming a system that can reason over enterprise knowledge. The real shift is the move from human-authored to AI-authored logic, under guardrails. Before Humans write explicit queries, design semantic models, orchestrate pipelines. Tools act as passive executors, doing exactly what they are told. Now Humans declare the intent. Agents determine the plan (how to answer) and execute across governed data, semantic and orchestration layers.

Mar 17, 2026

We Built the Benchmark. Now Let’s Evaluate the Fabric Data Agent for Real

This article shows how to move from a benchmark design to a real evaluation workflow for a Microsoft Fabric Data Agent. Starting from a 72-question benchmark built in a previous article for an Italian multilingual scenario, it explains how to complete the ground-truth dataset, run evaluate_data_agent on Fabric, inspect summary and row-level results, and use notebooks to operationalize the full process. A key insight is that part of the observed weakness may come not only from the Data Agent, but also from the evaluation layer itself. By inspecting the SDK source code and testing a stricter custom critic prompt, the article shows how evaluation reliability can improve significantly without changing the agent or the benchmark. Overall, the piece is a practical guide to benchmarking and evaluating Fabric Data Agents more rigorously, especially in multilingual business scenarios.

Mar 31, 2026

Microsoft Fabricで考える非構造データのAI活用

このビデオは、G-Corporationの永田凌真氏によって紹介され、Microsoft Fabricエコシステム内で非構造データを活用するAIの活用に焦点を当てています。セッションでは、AI FunctionsやData Agentを含む最新のデータアーキテクチャとAI実装戦略について、技術的な詳細を深く掘り下げています English : This video, presented by Ryomaru Nagata from G-Corporation, focuses on leveraging AI for unstructured data within the Microsoft Fabric ecosystem. The session provides a technical deep dive into modern data architecture and AI implementation strategies, including AI Functions and Data Agent

Feb 10, 2026

Configuring Fabric Data Agent to Accelerate Data to Decisions

In this session, attendees will explore how to build and configure a Fabric Data Agent from the ground up. We’ll walk through practical commands and functions while working with data sourced from a Lakehouse, review data source setup and sample queries, and showcase how easily a Fabric Data Agent can be incorporated into a multi-agent workflow using Microsoft Foundry.

Feb 5, 2026

Les Data Agents dans Microsoft Fabric

Dans l’océan des données, voir clair change tout. Sur Phare Data, on décrypte les services de data, d’analytics et d’IA, avec un ton accessible, des choix techniques assumés, et toujours une touche d’air marin. Que vous soyez architecte, analyste, data engineer, product owner, ou simplement curieux, Phare Data vous accompagne pour comprendre les enjeux réels, éclairer les compromis et prendre de meilleures décisions et parfois avec le cri des mouettes en bruit de fond.

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.

Mar 21, 2026

From Power BI to Conversational AI: Building Data Agents That Scales

Your Power BI semantic models already contain trusted business logic, metrics, and relationships. What if those same models could answer questions in natural language across Teams, Excel, and M365 Copilot without rebuilding everything? In this session, you'll see the complete journey from a standard Power BI semantic model to a conversational data agent deployed across multiple surfaces. We'll walk through: Preparing your semantic model for AI: Adding descriptions, AI instructions, and verified answers directly in Power BI Desktop Creating Fabric Data Agents: Turning your semantic model into an intelligent assistant with proper guardrails Deploying across M365: Making your agent accessible in Excel, Teams, and M365 Copilot Through a live demonstration using a real semantic model, you'll see how to handle time intelligence, variance calculations, and business-specific definitions so the AI understands your metrics the way your users do. We'll also cover what actually works (and what doesn't) when moving from visual analytics to conversational experiences. This isn't about replacing Power BI reports. It's about extending the work you've already done into new interaction patterns where they add real value.

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 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