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Question 185 - DAS-C01 discussion

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A financial services company is building a data lake solution on Amazon S3. The company plans to use analytics offerings from AWS to meet user needs for one-time querying and business intelligence reports. A portion of the columns will contain personally identifiable information (Pll). Only authorized users should be able to see plaintext PII data.

What is the MOST operationally efficient solution that meets these requirements?

A.
Define a bucket policy for each S3 bucket of the data lake to allow access to users who have authorization to see PII data. Catalog the data by using AWS Glue. Create two IAM roles. Attach a permissions policy with access to PII columns to one role. Attach a policy without these permissions to the other role.
Answers
A.
Define a bucket policy for each S3 bucket of the data lake to allow access to users who have authorization to see PII data. Catalog the data by using AWS Glue. Create two IAM roles. Attach a permissions policy with access to PII columns to one role. Attach a policy without these permissions to the other role.
B.
Register the S3 locations with AWS Lake Formation. Create two IAM roles. Use Lake Formation data permissions to grant Select permissions to all of the columns for one role. Grant Select permissions to only columns that contain non-PII data for the other role.
Answers
B.
Register the S3 locations with AWS Lake Formation. Create two IAM roles. Use Lake Formation data permissions to grant Select permissions to all of the columns for one role. Grant Select permissions to only columns that contain non-PII data for the other role.
C.
Register the S3 locations with AWS Lake Formation. Create an AWS Glue job to create an E TL workflow that removes the Pll columns from the data and creates a separate copy of the data in another data lake S3 bucket. Register the new S3 locations with Lake Formation. Grant users the permissions to each data lake data based on whether the users are authorized to see PII data.
Answers
C.
Register the S3 locations with AWS Lake Formation. Create an AWS Glue job to create an E TL workflow that removes the Pll columns from the data and creates a separate copy of the data in another data lake S3 bucket. Register the new S3 locations with Lake Formation. Grant users the permissions to each data lake data based on whether the users are authorized to see PII data.
D.
Register the S3 locations with AWS Lake Formation. Create two IAM roles. Attach a permissions policy with access to Pll columns to one role. Attach a policy without these permissions to the other role. For each downstream analytics service, use its native security functionality and the IAM roles to secure the Pll data.
Answers
D.
Register the S3 locations with AWS Lake Formation. Create two IAM roles. Attach a permissions policy with access to Pll columns to one role. Attach a policy without these permissions to the other role. For each downstream analytics service, use its native security functionality and the IAM roles to secure the Pll data.
Suggested answer: B

Explanation:

This solution meets the requirements because:

AWS Lake Formation is a fully managed service that allows you to build, secure, and manage data lakes on AWS1.You can use Lake Formation to register your S3 locations as data sources and catalog your data using AWS Glue1.

AWS Lake Formation provides fine-grained data permissions that enable you to control access to your data at the column or row level1.You can use Lake Formation to create two IAM roles and grant them different Select permissions based on the PII status of the columns1.

AWS Lake Formation integrates with various analytics services from AWS, such as Amazon Athena, Amazon Redshift, Amazon EMR, and Amazon QuickSight1.You can use these services to query and visualize your data in S3 using the IAM roles and permissions defined by Lake Formation1.

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asked 16/09/2024
Nuno Silva
38 questions
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