Data Engineering Associate with Databricks Practice Exam

What are the Table ACL permissions in Databricks?

1. Catalog, database, table, view, function, any file

2. Read, write, delete, execute

3. Owner, admin, user, viewer

4. Database, schema, collection, report

The correct answer is: Catalog, database, table, view, function, any file

The correct answer highlights the different levels of access control that can be applied to objects within Databricks. Table ACL (Access Control List) permissions allow for granular control over who can access specific resources like catalogs, databases, tables, views, functions, and even files stored within Databricks. This level of detail is essential in a collaborative data environment where different users may require different levels of access based on their roles or the nature of their work. Understanding this framework of Table ACL permissions enables organizations to enforce security and compliance effectively. By assigning specific access permissions to objects, organizations can protect sensitive data while still allowing team members to work with the data they need to perform their jobs. Each of the entities mentioned – catalog, database, table, view, function, and file – plays a crucial role in data management and security controls. The context of the other options does not align with the specific nature of Table ACL permissions. While "Read, write, delete, execute" relates to typical permissions associated with file systems or databases, it lacks the comprehensive breakdown of the types of data objects found in Databricks. Similarly, "Owner, admin, user, viewer" represents roles rather than the specific objects that can have ACL permissions assigned to them. Lastly