Sandeep Pawar

Jun 4, 2025

Automatically populate Data Agents with Semantic Model Synonyms

Automatically populate Data Agents with Semantic Model Synonyms, however note that synonyms are used by data agents. Excellent blog none the less on getting the data AI ready.

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.

Jan 10, 2026

Best Practices for Fabric Data Agent Development

A collection of best practices and design patterns for building production-ready data agents in Microsoft Fabric, including error handling, performance optimization, and security considerations.

Apr 1, 2026

Designing AI‑Ready Analytics with Microsoft Fabric Data Agents

s organizations accelerate their adoption of AI-powered analytics, a new challenge is emerging: how to expose trusted business data to AI—Copilot, data agents, and conversational analytics—in a way that is secure, cost-predictable, and architecturally sound. Most enterprises are already operating in a complex reality: Power BI reports connected to operational systems like Oracle, SAP, and SQL Server A mix of Import and DirectQuery semantic models Strong governance expectations around security, lineage, and cost control

Jan 28, 2026

Microsoft Fabric Copilot: Building a Foundation of Trust Before You Ask Questions!

The blog discusses why establishing a strong foundation of trust is essential before users begin asking questions to Microsoft Fabric Copilot. It emphasizes that Copilot’s effectiveness depends heavily on the quality, clarity, and governance of the underlying data and semantic models. The author explains how organizations should prepare their Fabric environment—through well‑modeled data, proper documentation, security, and metadata—so Copilot can generate accurate, reliable, and context‑aware responses. Overall, it’s a call to treat Copilot not as magic, but as a powerful layer built on top of disciplined data practices.

Mar 26, 2025

What We Learned Building a Real-World Fabric Data Agent

The post is a detailed, field‑tested account of building a real‑world Fabric Data Agent on top of a complex industrial supply‑chain dataset, highlighting what works, what breaks, and what requires deliberate engineering. It walks through six major lessons: why agent instructions—not data sources—determine answer quality; how Semantic Models and Ontologies complement each other; the pitfalls of asynchronous graph rebuilds; the importance of using binding property names in GQL; common GQL query‑generation failures; and the hidden requirement to use dbo. prefixes in SQL. Despite the rough edges of a preview product, the author argues that Fabric IQ’s architecture—unifying SQL, DAX, and GQL behind a governed semantic layer—is powerful and worth understanding deeply for anyone building enterprise‑grade AI analytics.

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

Microsoft Fabric Community Forum

Join the Microsoft Fabric community to ask questions, share solutions, and connect with other data agent builders.

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.

Fabric Data Agent Sample Notebooks

A collection of Jupyter notebooks and code samples demonstrating various data agent patterns and use cases in Microsoft Fabric.

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.

Dec 4, 2025

Analyzing Microsoft Fabric Data using an Azure AI Foundry Agent

In this Microsoft Reactor session, Ziggy demonstrates how to analyze Microsoft Fabric data using a Microsoft Foundry Agent and surface insights through a conversational AI experience. This is the third and final part of a series where we transform unstructured data—such as product reviews and customer call recordings—into actionable insights using Microsoft Fabric, Foundry Agent Service, and Power BI. You’ll learn how to: Create a Fabric Data Agent to query lakehouse data in plain English Connect Microsoft Foundry Agents to Fabric for secure enterprise data access Deploy your AI-powered agent to Microsoft Teams for internal collaboration Use sample queries and SQL generation for real-time insights Understand the architecture behind Fabric lakehouse, pipelines, and notebooks

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.

Aug 28, 2025

Connect Data Agents to Teams with Copilot Studio

You've built your Retrieval Augmentation Generation, or RAG, pattern Data Agent in Microsoft Fabric, but now you want to share it with your organization! How do you do that? Fear not! Bradley Ball aka ‪@SQLBalls‬ has got you covered! We walk through Microsoft Fabric creating the Data Agent, to Copilot Studio creating a connected Agent, to Publishing and approving in Teams!

Feb 6, 2025

Create your first Data Agent with SQL database in Fabric

Learn to create low code/no code Data Agents in less than 5 minutes with SQL DB

Aug 9, 2025

Extend Fabric Data Agents with Python SDK End to End Tutorial

Let's walk through and End to End tutorial for extending an existing Data Agent with Bradley Ball, aka ‪@SQLBalls‬. In this tutorial we will use the first two links to get and clone the GitHub repo and to use the code to substitute our questions for those hard coded in the tutorial. We also extend the tutorial to make a change to move from hard coded questions to a more interactive Q & A application!

Feb 1, 2026

Fabric Data Agent for Semantic Model

This video reviews the new Semantic Model Fabric Data Agent that as been added to our free GitHub training repo with 275 million rows of real data. The new Semantic Model Data Agent can be added with a few simple steps, and then you can compare and contrast the Lakehouse and Semantic Model Data Agents.

Mar 1, 2025

Fabric Data Agents 101

A beginner-friendly walkthrough covering the fundamentals of Fabric Data Agents — what they are, how to set them up, and how to start querying your data using natural language.

Jun 1, 2025

Fabric Data Agents and Beyond

Explores the broader vision for Fabric Data Agents, including advanced use cases, multi-source data access, integration with Azure AI Agent Service, and how agents go beyond simple Q&A to enable enterprise-scale AI workflows.

May 1, 2025

Microsoft Fabric Data Agents Explained

From query to conversation — demonstrates setting up a Fabric Data Agent, connecting it to a Lakehouse, customizing prompts, and using chat-based analytics to extract insights from your data in real time.

Jun 4, 2025

How to Set Up Fabric Data Agents in Microsoft Fabric

Discover how to configure Fabric Data Agents to streamline and manage your data movement across environments in Microsoft Fabric. In this tutorial, we’ll guide you through the installation, setup, and key use cases for Data Agents, helping you connect to on-premises sources and automate secure data flows. Perfect for Fabric admins and data engineers looking to enable hybrid data scenarios with ease. Hi, I’m David, the Managing Director of Level Up Your Data based in Brisbane, Australia and a Microsoft Data Platform MVP. I am passionate about the positive impact data can have on our lives, businesses, world economies, and the environment and enjoy sharing my knowledge with you.

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 1, 2025

Introduction to Microsoft Fabric Data Agents

Covers what Fabric Data Agents are, how they use generative AI for Q&A over your data, prerequisites, setup process, connecting semantic models, and how to publish agents for broader use across Microsoft 365 Copilot and Teams.

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.

Aug 26, 2025

Microsoft Fabric: Connect Data Agent to Azure AI Foundry

Data agent in Microsoft Fabric transforms enterprise data into conversational Q&A systems. It enables users to interact with their data through chat, to uncover actionable insights. One way to consume Fabric data agent is through Azure AI Agent Service, a core component of Azure AI Foundry and Bradley Ball, aka ‪@SQLBalls‬ , has got you covered!!

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 4, 2026

Optimizing the Costs of Fabric Data Agents

In this video you will learn how to find the costs of Fabric Data Agents, by looking at the Fabric Capacity Metrics App.

Dec 18, 2025

Publish Data Agents Directly to Microsoft 365

It's here! Fresh off of Microsoft Ignite 2025 we can now publish Data Agents directly to Microsoft 365 and Bradley Ball, aka ‪@SQLBalls‬ , has got you covered! This is a super simple process and we will walk through how to publish, what the interface looks like, and how to share it with Microsoft Teams!

Aug 9, 2025

Skip navigation fabric data agent Create Avatar image Turning Data into Insights with Copilot and Data Agents in Microsoft Fabric

We will explore AI functions in notebooks, which make it easy to apply enrichment such as summarization, sentiment analysis, and entity extraction with a single line of code. You will also see how AI-powered transforms on OneLake shortcuts can automatically process text files for summarization, translation, or PII detection without building pipelines. Finally, we will show how Data Wrangler provides an interactive way to clean and shape your data inside notebooks while generating reusable code. Through a live demo, you will see how these capabilities combine to help you deliver insights and intelligent features quickly for your hackathon project.

Dec 20, 2025

Wiring AI Agents to Enterprise Data with Azure AI Foundry + Fabric

This demo shows one concrete way to design a multi-agent system using Azure AI Foundry and Microsoft Fabric.

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.

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.

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.

Data Agent Inspector

App to review data agent diagnostic file.

Semantic Link Labs

An open-source toolkit for building semantic layers and connecting data agents to structured data sources in Microsoft Fabric.

Data Agent MCP

The Model Context Protocol (MCP) server is an emerging standard in the AI landscape that allows AI systems to discover and interact with external tools in a structured way. It plays a critical role in enabling AI models to access and use external knowledge and capabilities. By using MCP servers, AI systems can extend beyond their own data and reasoning. MCP servers provide a way to expose tools and services to AI systems in a consistent, discoverable manner. They help organizations integrate their knowledge into AI workflows.

Apr 17, 2026

𝗖𝗵𝗮𝘁 𝘄𝗶𝘁𝗵 𝘆𝗼𝘂𝗿 𝗱𝗮𝘁𝗮 in Copilot, Data Agents or Databricks One? 🤖

Is your data AI ready? Are your "consumers" ready for it? Don't let AI solely write your instructions, documentation and verified answers. You need a documentation system and process to steer the process. See the guide for links to notebooks, scripts and skills that take you further! My new favorite Tabular Editor C# Macro is on slide 5 😍 I'm happy to see that if you want to succeed with Chat with your data, optimizing and documenting semantic models are still (if not more) important.

Apr 18, 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.

Mar 16, 2026

Copilot vs Data Agents

Microsoft Fabric now gives us Data Agents - purpose-built, grounded on your actual data sources (Lakehouse, Warehouse, SQL DB, KQL DB), and fully customizable with AI instructions, example SQL queries, and tone/format control. Compare that to the standalone Copilot: broad access, but limited customization and no instruction support.

Apr 18, 2026

Data Agent to Data Memo

Experimented with a pipeline to explore the data autonomously, find insights, find second order signals, create a cohesive narrative that's grounded in the data & context, added an optimization layer using DSPy (Community) to tune it and converted to speech. No external APIs, services, 100% in hashtag#MicrosoftFabric . 🔊Listen, let me know. The novelty here is I used the recently published LLM-as-Verifier approach as a metric in GEPA to tune the narrative. (https://lnkd.in/g2Huycw9)

Mar 16, 2026

Data agent with SQL DB in Fabric

🚀 You launched your first SQL database in Fabric? Wondering what else you can do next? Imagine being able to chat with your data—or empowering your whole team to interact with your database using natural language. That’s where Data Agents in Microsoft Fabric come in. Internet is buzzing with folks building Data Agents – Here’s your chance to to be part of the excitement. 👇 Check out my quick video to see what’s possible when you let Data Agents do the heavy lifting. Join the conversation, share what you build next, and let’s inspire each other to keep innovating! hashtag#DataAgents hashtag#MicrosoftFabric hashtag#LowCode hashtag#NoCode hashtag#Innovation hashtag#SQLdatabaseinFabric https://lnkd.in/eYwtMrNN

Mar 16, 2026

Data Agents with Business Central Data

Ever wished you could ask natural language questions about your Business Central data and get instant insights? With the new Data Agent inside Microsoft Fabric, that’s now possible! In my latest blog, I dive into: ✅ How Data Agent connects to Business Central ✅ Why this is a game-changer for self-service analytics ✅ Practical examples of asking questions on your ERP data If you’re working with Microsoft Fabric and Business Central, this is a must-read!

Apr 14, 2026

Fabric Ontology with Data Agent

AI built my Fabric Ontology demo in under an hour! Thanks to GitHub Copilot, I have notebooks for loading Lakehouse tables with demo data, building a Fabric Ontology, and creating instructions for a Fabric Data Agent to query the whole thing. Visit my GitHub repo to see the prompts I used, how Ontology Playground helped, and the skills files that were created along the way.

Mar 11, 2026

From API to AI Agent: Turning Raw Data into Conversational Intelligence with Microsoft Fabric

Data agent on top of Oura health data to chat with your own health data

Mar 16, 2026

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

Khaled will be presenting at SQL Saturday ATL on data agents

Mar 16, 2026

How to build an AI agent in Fabric and Foundry to leverage your business data

If you have been waiting for a step‑by‑step tutorial to make an AI agent that “speaks” the language of your business data, this guide is for you. In this article I will show you how to: (1) build a Fabric Data Agent over your Fabric Lakehouse and (2) connect that agent to Microsoft Foundry to enable extended agent capabilities.

Mar 16, 2026

Multi-agent routing for Fabric Data Agents using Microsoft Foundry

Creating multi-agent architecture with data agent and Microsoft Foundry

Mar 26, 2026

What We Learned Building a Real-World Fabric Data Agent — The Honest Field Notes

The post is a detailed, field‑tested account of building a real‑world Fabric Data Agent on top of a complex industrial supply‑chain dataset, highlighting what works, what breaks, and what requires deliberate engineering. It walks through six major lessons: why agent instructions—not data sources—determine answer quality; how Semantic Models and Ontologies complement each other; the pitfalls of asynchronous graph rebuilds; the importance of using binding property names in GQL; common GQL query‑generation failures; and the hidden requirement to use dbo. prefixes in SQL. Despite the rough edges of a preview product, the author argues that Fabric IQ’s architecture—unifying SQL, DAX, and GQL behind a governed semantic layer—is powerful and worth understanding deeply for anyone building enterprise‑grade AI analytics.