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Answer: 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.
The correct answer is D, 'All of the above', because each of the SQL functions listed has its own strengths in data masking scenarios. The CASE WHEN function is versatile for conditional logic, IF ELSE is straightforward for simple conditions, and COALESCE is ideal for handling NULL values. Together, they can be orchestrated to meet complex requirements such as GDPR compliance, minimal performance impact, and dynamic role-based masking. This combination ensures a robust and flexible data masking solution in Databricks.
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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.
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