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Every Lakehouse in Microsoft Fabric comes with a SQL analytics endpoint, and almost everybody misunderstands it at first. People try to insert data into it and get an error. They create a table and it does not show up. Or they set up SQL security and then find out that Spark users can still read everything. In this video we build one simple mental model that explains all of those surprises: two doors into the same data. The Lakehouse is the Spark door, where you read and write. The SQL analytics endpoint is the SQL door, a read-only T-SQL interface over the same Delta tables. Spark owns the writes, the endpoint serves the reads.

We put the endpoint side by side with the Fabric Warehouse (same engine, very different job), go through what you can actually do with a read-only interface (queries, views, functions, stored procedures, Power BI, cross-workspace shortcuts, time travel), and then tackle the two famous gotchas: the metadata sync ("where is my table?") and the security catch, where SQL permissions only guard the SQL door and OneLake security is what secures the data itself. Then we jump into Fabric and see all of it live: the failed UPDATE, creating a view, refreshing the endpoint from the editor and from a pipeline activity, the new metadata sync setting, and a DENY in action with a Viewer account.

This is Topic 3 of the Lakehouse course inside Fabric Forge. Want to put the endpoint through its paces yourself? The hands-on exercise is waiting for you in the community (link at the top).

Topics covered:
What the SQL analytics endpoint is and why every Lakehouse gets one
Two doors into the same data: Spark door vs SQL door
SQL analytics endpoint vs Fabric Warehouse: same engine, different job
What you can do with a read-only endpoint: queries, views, functions, stored procedures
Power BI over the TDS endpoint and building your own semantic model
Cross-workspace queries with shortcuts and time travel with T-SQL
Gotcha 1: the metadata sync and the three reasons your table is missing
Forcing a refresh: the sync button, the REST API, the pipeline activity, the new metadata sync
Gotcha 2: SQL security only guards the SQL door, OneLake security guards the data
Live demo: the failed UPDATE, views, refresh, Viewer access and DENY

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