Databricks Certified Data Engineer - Professional
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In the context of a Databricks environment, you are tasked with implementing data masking for a dataset that contains sensitive customer information, including personally identifiable information (PII). The solution must comply with GDPR requirements, ensure minimal performance impact, and allow for dynamic masking based on user roles. Considering these constraints, which of the following SQL functions is the most versatile and effective for performing dynamic data masking in Databricks? (Choose one correct answer)
A
CASE WHEN - Allows for conditional logic to mask data based on specific conditions but lacks the simplicity for straightforward masking scenarios.
B
IF ELSE - Suitable for simple conditional checks to mask data but may not efficiently handle complex masking requirements or dynamic role-based access.
C
COALESCE - Effective for replacing NULL values with a default value but does not provide dynamic masking capabilities based on user roles.
D
All of the above - When used in combination, these functions can create dynamic views that perform comprehensive data masking based on user roles and permissions, addressing GDPR compliance, performance, and dynamic access requirements.