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Answer: Use Amazon S3 for data lake storage. Use AWS Lake Formation to restrict data access by rows and columns. Provide data access through AWS Lake Formation.
AWS Lake Formation provides centralized data access control for your data lake on S3. It allows you to define fine-grained permissions, including row-level and column-level security, that apply across multiple analytics services like Amazon Athena, Amazon Redshift Spectrum, and Amazon EMR natively, with the least operational overhead.
Author: Ritesh Yadav
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Question 47 A company needs to build a data lake in AWS. The company must provide row-level data access and column-level data access to specific teams. The teams will access the data by using Amazon Athena, Amazon Redshift Spectrum, and Apache Hive from Amazon EMR. Which solution will meet these requirements with the LEAST operational overhead?
A
Use Amazon S3 for data lake storage. Use S3 access policies to restrict data access by rows and columns. Provide data access through Amazon S3.
B
Use Amazon S3 for data lake storage. Use Apache Ranger through Amazon EMR to restrict data access by rows and columns. Provide data access by using Apache Pig.
C
Use Amazon Redshift for data lake storage. Use Redshift security policies to restrict data access by rows and columns. Provide data access by using Apache Spark and Amazon Athena federated queries.
D
Use Amazon S3 for data lake storage. Use AWS Lake Formation to restrict data access by rows and columns. Provide data access through AWS Lake Formation.
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