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CSA Loom — the Microsoft Fabric experience for Azure tenants where Fabric isn't yet available: lakehouses, warehouses, notebooks, semantic models, Activator rules, Data Agents, across Commercial, GCC, GCC-High, and DoD IL5

Tutorial: Data agent editor

CSA Loom data-agent editor — verified working against a live console by the UAT harness on 2026-07-01.

Open the editor

  1. Sign in to your CSA Loom Console (for example https://<your-console-host>).
  2. Open or create a workspace from the Workspaces page.
  3. Click + New item and choose Data agent from the catalog.
  4. The editor opens at /items/data-agent/<id>:

Data agent editor

What this editor does

A Data agent is conversational Q&A grounded in your data sources — warehouse, lakehouse, KQL, AI Search, graph, and semantic models. In Loom the Build tab binds up to 5 sources, each scoped with a real schema tree; Config Copilot, Test chat, Evaluate, Publish, Consume, Run inspector, and Monitoring round out the lifecycle. Azure-native — no Microsoft Fabric required.

Getting started

  1. Pick data sources — On the Build tab bind up to 5 sources — warehouse, lakehouse, KQL / Eventhouse, AI Search, graph, or semantic model — and give each instructions and example questions.
  2. Scope the schema — Expand each source's schema tree — real Tables / Views / Functions / Fields read live from the backend (Synapse INFORMATION_SCHEMA, ADX .show tables, AI Search index) — and check exactly which objects the agent may query. No freeform table strings.
  3. Draft with Config Copilot — The Config Copilot tab drafts instructions and source descriptions from your bound schema so grounding starts strong.
  4. Test questions — Use Test chat to ask sample business questions and verify the agent queries the right sources; the Run inspector shows each tool call and query.
  5. Evaluate and publish — Score the agent against a question set on Evaluate, then Publish and share the Consume endpoint; Monitoring tracks usage over time.

Learn more

Verified by the UAT harness