Fabric Data Agent Resources
Curated links, documentation, and learning materials for Fabric Data Agents
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
Fabric Data Agent Demo — Wide World Importers
Two sample Microsoft Fabric data agents built on the WideWorldImportersDW data warehouse. A simple agent with minimal instructions silently returns wrong answers for complex queries, while an advanced agent with full data model documentation handles them correctly — same LLM, same data, different instructions. The demo proves that agent instruction quality is the single biggest lever for accuracy when building data agents over enterprise data warehouses with SCD2 dimensions, bridge tables, and weighted allocations.
Hands On : Build a Direct Lake Model with Data Agents with 275M+ Healthcare Records
This solution demonstrates the capabilities of Microsoft Fabric using over 275 million rows of real-world healthcare data. It showcases how to leverage the Power BI Direct Lake connector to query large datasets stored in Delta Parquet format—without caching or a relational database. Fabric Data Agents have also been added for the Semantic Model and the Lakeouse or Warehouse. The Semantic Model is also optimized for Power BI Copilot, including the standalone version that functions as a SaaS MCP server for chatting on all of your content and data. The dataset used is the publicly available Medicare Part D Prescribers - by Provider and Drug, sourced from the Centers for Medicare & Medicaid Services (CMS). 🎥 Watch the full demo: YouTube Video https://youtu.be/2tLIGVZ4c8E
Ontology with Data Agent
This project provides a complete, end‑to‑end walkthrough for building a Microsoft Fabric Ontology demo—either by installing a ready‑made healthcare example or by creating your own custom ontology, lakehouse tables, demo data, and graph queries. It shows how to use tools like VS Code, GitHub Copilot, Semantic Link Labs notebooks, and the Fabric Ontology Playground to generate RDF models, orchestrate table creation, build a graph database, and construct multi‑hop GQL queries that highlight the strengths of graph reasoning. It also guides you through creating a Fabric Data Agent powered by your ontology, including AI instructions and sample prompts, enabling a fully functional demo environment in under an hour.