The door to your Databricks workspace is only as strong as its access control rules. One weak policy, and you risk exposure of sensitive datasets, source notebooks, and models. NDA Databricks Access Control is not just a checkbox—it’s the structure that decides who sees what, who edits what, and who can run code against shared compute resources.
Databricks access control starts at the workspace level. You set permissions on clusters, jobs, notebooks, tables, and the underlying storage layers. Configuring these correctly is critical when working under a non-disclosure agreement (NDA), where unauthorized access isn’t just a security event—it’s a breach of contract.
Workspace admins use role-based access control (RBAC) to assign rights. Users gain specific abilities only as needed:
- View for read-only access to notebooks or dashboards.
- Edit to modify code or configurations.
- Manage for full control, including deletion or permission changes.
Beyond RBAC, Databricks supports object-level access control through Unity Catalog. Here, you can grant or revoke privileges on individual tables, schemas, or catalogs. Unity Catalog enforces these rules across all clusters, preventing shadow access paths that bypass workspace policy.