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Exam AWS Certified Solutions Architect - Associate SAA-C03 All Questions

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Exam AWS Certified Solutions Architect - Associate SAA-C03 topic 1 question 341 discussion

A company has an Amazon S3 data lake that is governed by AWS Lake Formation. The company wants to create a visualization in Amazon QuickSight by joining the data in the data lake with operational data that is stored in an Amazon Aurora MySQL database. The company wants to enforce column-level authorization so that the company’s marketing team can access only a subset of columns in the database.

Which solution will meet these requirements with the LEAST operational overhead?

  • A. Use Amazon EMR to ingest the data directly from the database to the QuickSight SPICE engine. Include only the required columns.
  • B. Use AWS Glue Studio to ingest the data from the database to the S3 data lake. Attach an IAM policy to the QuickSight users to enforce column-level access control. Use Amazon S3 as the data source in QuickSight.
  • C. Use AWS Glue Elastic Views to create a materialized view for the database in Amazon S3. Create an S3 bucket policy to enforce column-level access control for the QuickSight users. Use Amazon S3 as the data source in QuickSight.
  • D. Use a Lake Formation blueprint to ingest the data from the database to the S3 data lake. Use Lake Formation to enforce column-level access control for the QuickSight users. Use Amazon Athena as the data source in QuickSight.
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Suggested Answer: D 🗳️

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K0nAn
Highly Voted 1 year, 4 months ago
Selected Answer: D
This solution leverages AWS Lake Formation to ingest data from the Aurora MySQL database into the S3 data lake, while enforcing column-level access control for QuickSight users. Lake Formation can be used to create and manage the data lake's metadata and enforce security and governance policies, including column-level access control. This solution then uses Amazon Athena as the data source in QuickSight to query the data in the S3 data lake. This solution minimizes operational overhead by leveraging AWS services to manage and secure the data, and by using a standard query service (Amazon Athena) to provide a SQL interface to the data.
upvoted 13 times
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jennyka76
Highly Voted 1 year, 4 months ago
Answer - D https://aws.amazon.com/blogs/big-data/enforce-column-level-authorization-with-amazon-quicksight-and-aws-lake-formation/
upvoted 10 times
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awsgeek75
Most Recent 5 months, 1 week ago
Selected Answer: D
https://docs.aws.amazon.com/lake-formation/latest/dg/workflows-about.html
upvoted 2 times
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Guru4Cloud
9 months, 3 weeks ago
Selected Answer: D
Use a Lake Formation blueprint to ingest data from the Aurora database into the S3 data lake Leverage Lake Formation to enforce column-level access control for the marketing team Use Amazon Athena as the data source in QuickSight The key points: Need to join S3 data lake data with Aurora MySQL data Require column-level access controls for marketing team in QuickSight Minimize operational overhead
upvoted 4 times
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LuckyAro
1 year, 4 months ago
Selected Answer: D
Using a Lake Formation blueprint to ingest the data from the database to the S3 data lake, using Lake Formation to enforce column-level access control for the QuickSight users, and using Amazon Athena as the data source in QuickSight. This solution requires the least operational overhead as it utilizes the features provided by AWS Lake Formation to enforce column-level authorization, which simplifies the process and reduces the need for additional configuration and maintenance.
upvoted 5 times
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Bhawesh
1 year, 4 months ago
Selected Answer: D
D. Use a Lake Formation blueprint to ingest the data from the database to the S3 data lake. Use Lake Formation to enforce column-level access control for the QuickSight users. Use Amazon Athena as the data source in QuickSight. https://www.examtopics.com/discussions/amazon/view/80865-exam-aws-certified-solutions-architect-associate-saa-c02/
upvoted 3 times
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