Hard1 markMultiple Choice
Domain 1.2: Security ControlsSecurityData LakeLake FormationMacie

AWS SAP-C02 · Question 44 · Domain 1.2: Security Controls

A financial institution is building a data lake on Amazon S3. They must enforce strict data governance. Specifically, they need to ensure that sensitive data (like credit card numbers) is automatically discovered and masked before analysts can query it via Amazon Athena. They also need to manage fine-grained access control (column-level and row-level) to the data. Which combination of services should be used? (Select TWO)

Answer options:

A.

Use Amazon Macie to automatically discover and classify sensitive data in the S3 buckets.

B.

Use AWS Lake Formation to define and enforce column-level and row-level access controls for Athena queries.

C.

Use AWS KMS to encrypt the specific columns containing sensitive data.

D.

Use Amazon GuardDuty to monitor S3 data access patterns and block unauthorized queries.

E.

Configure S3 Bucket Policies to restrict access to specific rows in the CSV files.

F.

Use AWS Glue DataBrew to continuously mask data in real-time during Athena queries.

How to approach this question

Identify the service for data discovery (Macie) and the service for fine-grained data lake permissions (Lake Formation).

Full Answer

Amazon Macie is a data security service that discovers sensitive data in S3. AWS Lake Formation simplifies setting up a secure data lake. It allows you to define fine-grained access controls, including column-level and row-level security. When analysts query the data using Amazon Athena, Lake Formation enforces these policies, ensuring users only see the data they are authorized to view.

Common mistakes

Thinking S3 bucket policies or KMS can provide column/row-level security.

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