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.
Co-author: Alexei Robsky, Data Scientist Manager Overview As organizations increasingly rely on real-time data to drive decisions, the need for intelligent, responsive systems has never been greater. At the heart of this transformation is Fabric Real-Time Intelligence (RTI), a platform that empowers users to act on data as it arrives. Today, we’re excited to announce …
Continue reading “Introducing MCP Support for Real-Time Intelligence (RTI) “
Introduction Whether you’re building analytics pipelines or conversational AI systems, the risk of exposing sensitive data is real. AI models trained on unfiltered datasets can inadvertently memorize and regurgitate PII, leading to compliance violations and reputational damage. This blog explores how to build scalable, secure, and compliant data workflows using PySpark, Microsoft Presidio, and Faker—covering …
Continue reading “Privacy by Design: PII Detection and Anonymization with PySpark on Microsoft Fabric”
