Fabric Data Agent

#fabric

15 items tagged with "fabric"

đź“„ Articles

đź“„ article
linkedin.com

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.

Author: Pablo Junco Boquer
đź“„ article
microsoftlearning.github.io

Jan 1, 2026

Chat with your data using Microsoft Fabric data agents

Chat with your data using Microsoft Fabric data agents A Microsoft Fabric data agent enables natural interaction with your data by allowing you to ask questions in plain English and receive structured, human-readable responses. By eliminating the need to understand query languages like SQL (Structured Query Language), DAX (Data Analysis Expressions), or KQL (Kusto Query Language), the data agent makes data insights accessible across the organization, regardless of technical skill level.

Author: Microsoft Learn
đź“„ article
lucazavarella.medium.com

Mar 14, 2026

Building a Spider2-Inspired Benchmark to Measure the Real Robustness of a Fabric Data Agent in Italian

This article moves from working demos to measurable reliability by introducing a Spider2-inspired benchmark for evaluating a Fabric Data Agent in Italian. It explains why manual spot checks are not enough, and shows how to design a more rigorous evaluation framework that separates already-taught patterns from true generalization. The result is a practical benchmark design for assessing multilingual Fabric Data Agents beyond isolated successful examples.

Author: Luca Zavarella
đź“„ article
medium.com

Jan 12, 2026

Creating Data Agent in Microsoft Fabric - First Impression

The article walks us through the creation of data agent for first time user and explores various ways to play around data agent.

Author: Shresth Shukla
đź“„ article
azureops.org

Jan 1, 2026

Data Agent in Microsoft Fabric – Here’s How it Works by Azure Ops

Data Agent in Microsoft Fabric – Here’s How it Works Ever wished you could just ask your data questions in plain English and get instant, intelligent answers? With Microsoft Fabric’s new Data Agent, that’s not just possible, it’s powerful. In this post, I’ll walk you through how I built a Fabric Data Agent on top of the standard AdventureWorksDW dataset, and how you can too, even if you’re a complete beginner.

Author: AruzeOps.Org
đź“„ article
medium.com

Mar 4, 2026

Fabric Data Agents Are English-First (For Now): A Hands-On Guide to Configuring One on Zava DIY for Non-English Users

This article provides a hands-on, incremental guide to configuring a Microsoft Fabric Data Agent on the Zava DIY dataset for non-English users, while keeping the agent grounded in an English-first setup. It shows how to improve reliability step by step through data source descriptions, agent instructions, domain constraints, formatting rules, and validated example queries, then extends the configuration with a practical "translate in, translate out" approach. The result is a reproducible quick-win pattern for making the agent more analytics-ready across languages without introducing external translation layers or custom front ends.

Author: Luca Zavarella
đź“„ article
community.fabric.microsoft.com

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.

Author: Jennifer Ratten
đź“„ article
bakertilly.com

Mar 31, 2025

Implementing Data Agent in Microsoft Fabric for comprehensive business insights

Leveraging the semantic model for business insights The semantic model in Microsoft Fabric plays a crucial role in transforming raw data into meaningful business insights. By accessing the semantic model, Data Agent can understand and interpret complex data relationships, providing a unified view of the data that aligns perfectly with current reporting and analytical needs.

Author: Chris Wagner
đź“„ article
medium.com

Apr 7, 2026

New article: Which Verdicts Changed, and Why: a Row-Level Audit of Fabric Data Agent Evaluation

The author performs a detailed row‑level audit of a 72‑question benchmark to understand why evaluation verdicts changed after fixing errors in the benchmark itself. Many initial “failures” turn out to be caused by faulty ground truth, ambiguous phrasing, or inconsistent casing rules rather than true Data Agent mistakes. After refining benchmark wording, tightening Agent instructions, and clarifying metric definitions, accuracy rises to 97.2%. The few remaining errors stem from extremely complex multi‑step prompts and ambiguous schema references, revealing limits of the underlying model rather than flaws in the benchmark.

Author: Luca Zavarella
đź“„ article
medium.com

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.

Author: Jyotiprakash Behera
đź“„ article
medium.com

Jan 2, 2026

Using Microsoft Fabric Data Agent in Non-English Languages: A Practical Exploration

This article examines what Microsoft Fabric Data Agent's current non-English limitation means in practice, using Italian as a concrete business scenario. Rather than stopping at the official "English-first" guidance, it presents three pragmatic patterns for enabling multilingual experiences today: English instructions with translate-in/translate-out behavior, Copilot Studio as a multilingual front-end, and a translation gateway built around the Data Agent API. The goal is to help teams choose the right architecture for multilingual adoption without overestimating native language support.

Author: Luca Zavarella
đź“„ article
lucazavarella.medium.com

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.

Author: Luca Zavarella

đź“… Events

đź“… event
meetup.com

Apr 16, 2026

Designing Trusted Fabric Data Agents - Part 1

This four‑part series guides attendees through the intricacies of Microsoft Fabric Data Agents - from understanding how agents reason over data, to designing AI‑ready data foundations, selecting the right consumption architectures, and operating agents safely at scale. Participants will learn how to move beyond prompt‑level experimentation to system‑level thinking, how agent reasoning, semantic modeling, architectural patterns, and governance controls work together to produce reliable, explainable, and compliant AI‑driven outcomes. Each session builds on the last, equipping teams with practical frameworks, patterns, and checklists to confidently deploy Fabric Data Agents across diverse audiences while managing risk, trust, and performance. Part 1 or 4: A guided tour of why Fabric Data Agents represent a shift from human-authored queries to AI-authored execution logic under guardrails. Learn what a data agent is (and is not), how it fits into the Fabric ecosystem, and how the agent reasoning loop plans and executes grounded answers across governed Fabric artifacts.

đź“… event
lodestar.eu

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.

đź’Ľ LinkedIn Posts

đź“„ article
linkedin.com

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

Author: Mohammad Al-Qinneh