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Answer: Partition data by geography in a global lakehouse, implementing row-level security to enforce data access controls based on user location.
The optimal solution involves partitioning data by geography within a global lakehouse and applying row-level security to manage access based on the user's location. This method ensures data is segregated according to regional regulations while maintaining centralized storage. Row-level security restricts data access to authorized users only, enhancing compliance and privacy. Additionally, this approach improves analytical performance by enabling queries to target specific geographical partitions, thereby reducing processing load and speeding up response times. This strategy effectively balances compliance with performance in a cross-geographical data analysis context under stringent data locality laws.
Author: LeetQuiz Editorial Team
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When designing a data lakehouse for cross-geographical data analysis with strict data locality regulations, what is the best approach to ensure data compliance while optimizing analytical performance across different regions?
A
Utilize a federated query system across regional lakehouses, caching common datasets in each region for performance.
B
Partition data by geography in a global lakehouse, implementing row-level security to enforce data access controls based on user location.
C
Replicate data across regional lakehouses, applying data masking and anonymization to comply with local regulations.
D
Implement geo-partitioning with automated data lifecycle policies that move data to specific regional lakehouses based on access patterns.
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