How to force Lakehouse schema to SQL Endpoint ?

Hi VoltesDev 

You can try the following solutions to resolve such synchronization issues.

Refresh/Refresh Process: SQL Endpoint may need to be refreshed manually. Right-click on the SQL Endpoint view and select “Refresh”.
Cache Cleanup: Sometimes the Fabric system may have cache issues. Refresh your browser session or log out and log back in.
REFRESH TABLE Command: Run the following command from SQL Endpoint:
sqlREFRESH TABLE [table_name]

OneLake Synchronization Delay: In Fabric, it may take some time for OneLake to synchronize systems. Wait a few minutes and check again.
Clear Spark Cache: On Notebook, run these commands:
pythonspark.sql("REFRESH TABLE [table_name]")
# or
spark.catalog.refreshTable("[table_name]")

Force Update Table Metadata: Resave the table to force changes:
pythondf = spark. read.table("[table_name]")
df.write.mode("overwrite").saveAsTable("[table_name]")

Microsoft Support: If the problem persists, this behavior may be a Fabric service issue and you may need to contact Microsoft support.

These synchronization issues may occur from time to time as Fabric is a preview/new service.