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Answer: Create a dynamic view that includes all columns and use row-level security (RLS) to conditionally mask sensitive data based on the user's role or permissions.
Option B is the correct approach because it dynamically masks sensitive data based on the user's role or permissions using row-level security (RLS), without permanently altering the original dataset. This solution is cost-effective, as it does not require additional storage for modified datasets, scalable, as it can easily accommodate changes in user roles or permissions, and compliant with data protection regulations, as it ensures sensitive data is only accessible to authorized users. Options A, C, and D either do not provide dynamic masking based on user roles, permanently alter the original dataset, or introduce unnecessary costs and complexity.
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You are tasked with designing a solution for a financial services company that needs to share a large dataset containing customer information, including sensitive data such as social security numbers, with various departments within the organization. The solution must ensure that sensitive data is dynamically masked based on the user's role or permissions, without permanently altering the original dataset. Additionally, the solution should be cost-effective, scalable, and comply with data protection regulations. Which of the following approaches best meets these requirements? (Choose one option)
A
Implement a static view that excludes sensitive columns entirely and provide access to this view for all users, regardless of their role or permissions.
B
Create a dynamic view that includes all columns and use row-level security (RLS) to conditionally mask sensitive data based on the user's role or permissions.
C
Create a copy of the dataset with sensitive data permanently removed and provide access to this copy for users who do not require access to sensitive information.
D
Use a third-party data masking tool to permanently mask sensitive data in the original dataset before sharing it with any users.