Before building a new pipeline, an analytics engineer must find which existing Fabric data items across the tenant already hold customer order data, review their owners and sensitivity, and decide whether to reuse one rather than re-ingest the source. The engineer wants a single in-product surface that lists and lets them explore discoverable data items tenant-wide. Which feature should they use?
- AThe deployment pipeline view, which lists every Fabric data item across the tenant with its owner and sensitivity so engineers can browse and reuse existing data.
- BThe "OneLake" catalog, which presents discoverable data items across the tenant with owner and sensitivity information so engineers can explore and choose what to reuse. Correct
- CThe Real-Time hub, which catalogs every Fabric data item tenant-wide with owner and sensitivity details so engineers can discover and reuse existing order data.
- DWorkspace settings, which expose a tenant-wide list of all data items with their owners and sensitivity so engineers can locate and reuse existing order data.
Why A is wrong: A deployment pipeline moves content between development, test, and production stages of one workspace; it is not a tenant-wide discovery surface for finding and exploring existing data items.
Why B is correct: The "OneLake" catalog is the in-product surface for discovering data items across the tenant, showing ownership and governance details, which is exactly what the engineer needs to find and reuse existing order data.
Why C is wrong: The Real-Time hub centralises streaming sources and event streams, not the broad catalog of all data items, so it is the wrong surface for discovering an existing order table to reuse.
Why D is wrong: Workspace settings govern one workspace and do not provide a cross-tenant catalog of discoverable items, so they cannot surface order data held in other workspaces.