Data plays a critical role in agentic AI, enabling AI agents to operate independently, make informed decisions, and take meaningful actions. And that’s why we are expanding capabilities and deepening integrations between our data and AI platforms.
Starting today, organizations can use Azure AI Foundry to connect customized, conversational agents, created in Fabric. A critical component of Azure AI Agent Service is the ability to securely ground AI agent outputs in enterprise knowledge, so that responses are accurate, relevant, and contextually aware. Data agents in Fabric, formerly known as AI skills, can retrieve knowledge across different data sources – from lakehouse and warehouse data to Power BI semantic models and KQL databases – using a number of specialized query language tools that help AI to generate SQL, KQL and DAX to extract, process, and present data effectively and delivers precise, actionable insights. Fabric data agents can determine when to use specific data, how to combine it, and what insights matter most.
By combining Fabric’s sophisticated data analysis over enterprise data with Azure AI Foundry’s cutting-edge GenAI technology, businesses can create custom conversational AI agents leveraging domain expertise. This seamless integration enables organizations to develop agents that are not only based on unstructured data in Azure AI Search or SharePoint but also integrate with structured and semantic data in Microsoft OneLake, thereby enhancing data-driven decision-making.
Customers like NTT DATA are leveraging data agents in Microsoft Fabric to extract real time insights. NTT DATA built a suite of HR-focused data agents, helping users interact directly with real-time data to uncover patterns in staffing, chargeability, and productivity.
“We see data agents as a conversational capability layer we can use to ‘talk’ to our data, understand it, and derive different insights in support of our daily decision making. By significantly improving real-time actionable insights, Azure AI and Fabric help elevate business outcomes as well as human potential.”
Genis Campa, Head of Data Products Strategy, NTT DATA
We invite you to explore the preview and experience firsthand how this unified approach can transform your data into a powerful asset for more insightful decision-making.
Most enterprise data lives in free text – tickets, contracts, feedback, clinical notes, and more. It holds critical information but doesn’t fit into the structured tables that pipelines expect. Traditionally, extracting structure meant rule-based parsers that break with every format to change, or custom NLP models that take weeks to build. LLMs opened new possibilities, …
Continue reading “ExtractLabel: Schema-driven unstructured data extraction with Fabric AI Functions”
Welcome to the February 2026 Microsoft Fabric update! This month brings a wide range of enhancements across the Fabric platform—from improvements to the OneLake Catalog and developer experiences, to meaningful updates in Data Engineering, Data Factory, Real‑Time Intelligence, and more. Whether you’re building, operating, or scaling solutions in Fabric, there’s plenty here to explore. And …
Continue reading “Fabric February 2026 Feature Summary”
