Understand Column-Level Masking and Row-Level Security to Restrict Data Visibility Based on User Groups. DATA-ENGINEER-ASSOCIATE Practice Questions (Page 1)

Questions 1–5

1. 1foundation · easy

   Which SQL statement is used to create a masking policy in Databricks?

   • ACREATE MASK FUNCTION policy_name AS (val STRING) RETURNS STRING -> ...
   • BCREATE COLUMN POLICY policy_name AS (val STRING) RETURNS STRING -> ...
   • CCREATE MASKING POLICY policy_name AS (val STRING) RETURNS STRING -> ...
   • DCREATE POLICY policy_name ON COLUMN val AS (val STRING) RETURNS STRING -> ...
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2. 2foundation · easy

   Which scenario is best suited for row-level security?

   • AA user should be prevented from deleting rows
   • BA table should be encrypted at rest
   • CA sales team should only see records for their own region
   • DA user should not see the salary column in an employee table
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4. 3foundation · easy

   What is a key benefit of combining column masking and row-level security?

   • AIt improves query performance
   • BIt eliminates the need for user permissions
   • CIt automatically encrypts all data in the table
   • DIt provides comprehensive data visibility restrictions at both the row and column level
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5. 4foundation · easy

   What is the primary purpose of row-level security in Databricks?

   • ATo hide specific columns from users
   • BTo encrypt data in transit
   • CTo compress data to save storage
   • DTo filter which rows a user can see in a table
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6. 5expert · hard

   You have a masking policy 'mask_email' applied to the 'email' column of the 'customers' table. The policy currently masks the email for all users except the 'support' group. You need to change the policy so that the 'sales' group also sees the full email, but you must not disrupt the existing policy for the 'support' group. What is the best approach?

   • ACreate a new masking policy and apply it to the column, overriding the old one.
   • BDrop the masking policy and create a new one that includes both groups, then reapply it to the column.
   • CGrant the 'sales' group SELECT permission on the table to bypass the masking policy.
   • DUse ALTER MASKING POLICY to modify the policy to include the 'sales' group in the condition that returns the actual value.
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