Issue sharing report built off Databricks Mirrored Catalog

Hi jaredneedshelp,
You're encountering this issue because when using a Databricks mirrored catalog (or Lakehouse with shortcuts) in a Fabric workspace, the underlying Direct Lake mode enforces strict security at the data level. Even if users have access to the semantic model and report in a separate workspace, they still need explicit access to the Lakehouse that holds the mirrored catalog data. Simply assigning viewer permissions to the workspace containing the semantic model is not sufficient, as the Direct Lake connection attempts to query the source data directly from the lakehouse at runtime. 

To resolve this without granting full access to the original lakehouse workspace, you can assign item-level permissions to the Lakehouse itself (not the entire workspace) by sharing the lakehouse directly with the user group and granting them read access. This allows them to query the Direct Lake tables through the semantic model while keeping workspace-level access restricted. Alternatively, consider materializing key data into a new Lakehouse or using Import or DirectQuery mode as a workaround if security separation must be strictly enforced.