Use Masking Techniques as Guard Rails to Meet a Performance Objective GENERATIVE-AI-ENGINEER-ASSOCIATE Practice Questions (Page 2)

Questions 6–10

1. 6foundation · easy

   A data engineer wants to mask a phone number column so that only the last four digits are visible, e.g., 'XXX-XXX-1234'. Which approach is most appropriate?

   • AUse the `regexp_replace()` function to remove the first six digits.
   • BUse the `substring()` function to extract the last four digits and discard the rest.
   • CUse the `mask()` function with a custom pattern that preserves the last four digits.
   • DUse the `replace()` function to replace all digits with 'X'.
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2. 7application · medium

   A government agency stores citizen records in Unity Catalog. The agency needs to ensure that social security numbers (SSNs) are visible only to users in the 'case_worker' role. Other users should see a masked version showing only the last four digits. The agency also wants to ensure that the masking is enforced even if a user creates a new view or table from the source data. Which approach should they take?

   • ACreate a static masked copy of the table and grant all users access to the copy.
   • BUse row-level security to restrict access to rows containing SSNs for non-case-worker users.
   • CApply a dynamic masking function on the SSN column with an exemption for the 'case_worker' role.
   • DEncrypt the SSN column with a customer-managed key and provide the key to all users.
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4. 8foundation · easy

   What is a potential performance impact of dynamic data masking on query execution?

   • AIt can increase query execution time because masking functions are applied to the result set at query time.
   • BIt can cause queries to fail if the masking function is not optimized.
   • CIt has no impact on query performance because masking is applied at the storage layer.
   • DIt can decrease query execution time because masking reduces the amount of data returned.
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5. 9foundation · easy

   How does combining masking with role-based access control (RBAC) enhance data governance in Databricks?

   • AIt ensures that all users see the same masked version of the data, regardless of their role.
   • BIt allows masking rules to be applied dynamically based on the user's role, so different roles see different levels of data visibility.
   • CIt encrypts the data so that only users with the appropriate role can decrypt it.
   • DIt replaces the need for access control lists by automatically granting permissions to users based on their role.
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6. 10foundation · easy

   Which strategy can help minimize the performance impact of masking in a Databricks environment?

   • AUse static masking instead of dynamic masking for all queries.
   • BLimit masking to only the columns that contain sensitive data and use efficient masking functions.
   • CApply masking to all columns in the table, even if they do not contain sensitive data.
   • DAvoid using masking altogether to ensure the best performance.
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