In this training-focused walkthrough, Pragmatic Works' own Mitchell Pearson introduces the rapidly evolving world of Microsoft Fabric Data Agents. As the concept of “agents” continues to gain momentum across the industry, Mitchell breaks down what data agents are, how they function, and how organizations can begin using them today— even while the feature remains in preview. This introductory guide provides a practical look at configurations, prerequisites, and deployment options to help learners quickly build their first agent.
Microsoft Fabric Data Agents act as a powerful AI-driven Q&A interface embedded directly into the Fabric platform. Using generative AI, these agents allow users to ask natural-language questions that are answered based on the organization’s own data. Mitchell explains that fabric data agents serve as a bridge between business users and semantic models, enabling quick insights without requiring a dedicated analyst to build custom reports.
Mitchell emphasizes a few required steps before creating your first Fabric Data Agent:
If a user enters Fabric and cannot create an agent, these prerequisites are typically the reason. Once enabled, the agent creation process becomes quick and accessible to any Fabric workspace contributor.
Mitchell demonstrates the workflow by navigating to a workspace and selecting New Item → Agent. Even though the feature is still in preview, it is fully functional. He names the agent and moves straight into the setup steps, which primarily consist of:
He stresses that while creating an agent is fast, achieving accurate results requires a well-designed model. Poorly structured data leads to unclear or inconsistent AI answers, so data preparation remains critical.
To demonstrate functionality, Mitchell asks the agent to calculate Total Sales by Year. Because the semantic model already includes the appropriate measure, the agent returns the results immediately. One standout feature is Fabric’s transparency—users can expand the result and view:
This level of visibility is particularly valuable for validation, testing, and troubleshooting. For analytics teams, it ensures that outputs align with expected logic rather than relying on assumptions about how the AI constructed the answer.
Once built, data agents are not limited to the Fabric portal. Mitchell explains several ways end users can consume data agents, including:
Publishing an agent to the Microsoft 365 Agent Store enables organization-wide access, allowing users to interact with it directly inside M365 Copilot. For Teams-based scenarios, Mitchell outlines how a parent Copilot Studio agent can route queries to different Fabric data agents—a flexible approach used in recent customer engagements.
Mitchell shares that many organizations are eager to adopt Fabric Data Agents even while the service is in preview. Engagements often involve:
One surprising insight is that customers often assume agent development belongs in later phases of their digital transformation. Instead, Mitchell clarifies that once data is migrated and modeled, agents can be created almost immediately—accelerating ROI.
As this video serves as an introductory guide, Mitchell closes by hinting at an upcoming full series on Fabric Data Agents. These future episodes will dive deeper into:
For learners and organizations exploring Microsoft Fabric, this introduction offers a clear and actionable starting point. Pragmatic Works remains committed to delivering hands-on guidance to help teams unlock the full potential of AI-driven analytics.
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