Databricks Certified Data Engineer - Professional
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In a scenario where you are tasked with implementing data masking for a financial dataset in Databricks to comply with GDPR and ensure that sensitive information such as personal identification numbers and financial details are protected, while still allowing analysts to perform necessary analytics on the data. The solution must also be cost-effective and scalable to accommodate future data growth. Which of the following approaches would be the BEST to achieve these objectives? (Choose one option)
A
Create a static view that redacts all sensitive information and provide access to all users, ensuring simplicity but potentially limiting analytical capabilities due to the lack of dynamic data access.
B
Use dynamic views to control access to rows and columns based on user roles and permissions, allowing for fine-grained access control and ensuring that users only see the data they are authorized to, without the need for data duplication.
C
Encrypt the entire dataset and only decrypt it when a user with the highest level of access requests it, which may introduce unnecessary complexity and performance overhead for routine analytics.
D
Remove all sensitive information from the dataset and replace it with generic placeholders, which may significantly reduce the dataset's utility for analytics and decision-making.