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Answer: Segment sensitive data into a dedicated, secured area of the lakehouse, applying column-level security and masking where necessary.
Segmenting sensitive data into a dedicated, secured area of the data lakehouse is a common best practice for handling highly sensitive personal data subject to regulatory compliance. This approach allows for better control and monitoring of access to the sensitive data, reducing the risk of unauthorized access or data breaches. Applying column-level security and masking within this dedicated area ensures that only authorized users have access to specific columns containing sensitive information. This fine-grained access control helps enforce data privacy and compliance with regulations such as GDPR or HIPAA. By keeping sensitive data separate from non-sensitive data, organizations can more easily manage and secure the most critical information. This also simplifies compliance efforts by focusing security measures on the most sensitive parts of the data lakehouse. Overall, this approach strikes a balance between ensuring compliance with regulations and maintaining usability for analytics. It provides a strong security model for protecting sensitive data while still allowing for efficient data analysis and insights.
Author: LeetQuiz Editorial Team
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How can a data lakehouse storing highly sensitive personal data subject to regulatory compliance best ensure compliance while maintaining usability for analytics?
A
Store sensitive data in encrypted form within the same tables as non-sensitive data, decrypting on-the-fly during query execution.
B
Segment sensitive data into a dedicated, secured area of the lakehouse, applying column-level security and masking where necessary.
C
Encrypt all data at rest and in transit, applying fine-grained access control at the file level based on user roles.
D
Utilize a hybrid approach, keeping sensitive data in a fully encrypted and isolated storage account with restricted access, and non-sensitive data in a general-purpose lakehouse area.
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