The Tool Desk
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What Microsoft announced at Ignite 2025
In its November 18, 2025 Ignite announcement, Microsoft described Fabric IQ as a way to connect analytical, time-series, location-based, and operational data through a shared model tied to business meaning. The intended result, in Microsoft’s description, is a live, connected view of a business that people and AI agents can use. Microsoft also said that existing Power BI data models can help provide agent context for organizations already using Power BI. These are product descriptions, not independently measured performance results.
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The practical distinction is between making data available and making it interpretable. A table may contain customer IDs, order dates, targets, or asset readings; business context defines what those things mean, how they connect, and which measures or actions apply. Fabric IQ aims to make that context usable across analytics and operational experiences rather than requiring every tool or agent to interpret raw data on its own.
How Fabric IQ is structured
Microsoft’s current Fabric IQ overview describes three connected layers. Together they link data storage, established business measures, and a model of operational concepts.
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OneLake: the unified data foundation
OneLake connects enterprise data and makes it available to Fabric workloads and related agent experiences. It is the foundation on which the other layers can work; it does not, by itself, define what a business term means.
Power BI semantic models: governed measures and dimensions
Power BI semantic models organize data into curated measures, hierarchies, and dimensions. Microsoft says ontologies can be generated from or aligned with these models, helping preserve consistent business terms and key performance indicators (KPIs). For organizations with established semantic models, this offers a route to reuse existing definitions as context for agents rather than treating each agent as a separate source of business logic.
Ontology: business entities, relationships, and actions
An ontology represents business entities, their properties and relationships, and relevant rules and actions. It provides a shared business language that people and agents can use to reason about business information and, where configured, take action. For example, the value is not merely knowing that two datasets contain related identifiers; it is representing how the underlying business entities relate and what those relationships mean.
Microsoft’s current overview labels ontology as preview. Release states can change, and Microsoft release notes show Fabric IQ capabilities continuing to evolve, including conversational analytics and planning updates. Check the current Microsoft documentation and release notes before relying on a particular capability or its availability.
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1Repair Windows errors before they cause bigger problems2Fix the driver behind crashes, sound loss and screen glitches3Clear out junk files and repair common Windows errorsFabric IQ is not one agent
Fabric IQ describes a broader business-context and data capability set. Microsoft documents several agent patterns that can use ontology, with different interaction styles and customization needs:
| Option | Best suited to | Typical interaction |
|---|---|---|
| Fabric operations agent | Watching business goals and responding to changes | Continuous monitoring, alerts, and configured actions |
| Fabric data agent | Questions about governed Fabric data | Interactive natural-language question and answer |
| Foundry agent | Developer-built solutions needing customization or enterprise-system integration | Custom agent with tool calling and integrations |
| Copilot Studio agent | Low-code conversational experiences and workflow automation | Conversational interaction and automated workflows |
| Custom MCP-compatible agent | External or custom agents that need to connect through Model Context Protocol (MCP) | Agent integration with ontology through MCP |
Choose by workflow first: a need to monitor continuously differs from a need to answer questions on demand. Then consider whether the team needs low-code configuration or developer-level customization, and whether the agent should live in a built-in Fabric experience or connect from an external system. These are integration patterns, not interchangeable product names; Microsoft’s ontology integration guide describes the available options.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What to check before connecting an agent
Prerequisites depend on the integration path. In particular, Microsoft’s documented Fabric data agent capacity requirements should not be assumed to apply identically to every Foundry or external-agent configuration.
For a Fabric data agent
- Use paid Fabric capacity at F2 or higher, or Power BI Premium capacity at P1 or higher with Fabric enabled.
- Place the workspace in a region that supports the full Fabric stack.
- Confirm that users have the required licenses and access to the data the agent will use.
- Review cross-geo processing and storage settings where they apply to the workspace and data.
For a Foundry connection
- Deploy a Foundry model and confirm that the connection has appropriate Fabric access.
- Review the data flow and the applicable identity, permission, and governance controls.
- Account for possible Foundry costs separately; Microsoft’s guidance warns that Foundry use can incur costs.
Governance and data-boundary considerations
A connection that works technically is not automatically appropriate for every dataset or geography. Microsoft warns that Foundry processing may take data outside the Fabric compliance boundary or geographic region, subject to Foundry’s data-handling terms. Before deployment, an organization should establish which data the agent can access, which identities it uses, where processing occurs, and whether cross-geo settings or organizational policies permit that flow. Avoid treating the integration as inherently compliant or risk-free; suitability depends on the chosen setup and the organization’s requirements.
Fabric IQ’s central promise is shared business context across data, analytics, and agent experiences. Whether that promise is useful in a specific deployment depends on the quality and governance of the underlying data and definitions, the integration pattern selected, and the feature’s release status at the time it is used.
Quick Recap
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