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An airline company is collecting metrics about flight activities for analytics. The company is conducting a proof of concept (POC) test to show how analytics can provide insights that the company can use to increase on-time departures. The POC test uses objects in Amazon S3 that contain the metrics in .csv format. The POC test uses Amazon Athena to query the data. The data is partitioned in the S3 bucket by date. As the amount of data increases, the company wants to optimize the storage solution to improve query performance. Which combination of solutions will meet these requirements? (Choose two.)
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Question 110 - DEA-C01 discussion

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A company implements a data mesh that has a central governance account. The company needs to catalog all data in the governance account. The governance account uses AWS Lake Formation to centrally share data and grant access permissions.

The company has created a new data product that includes a group of Amazon Redshift Serverless tables. A data engineer needs to share the data product with a marketing team. The marketing team must have access to only a subset of columns. The data engineer needs to share the same data product with a compliance team. The compliance team must have access to a different subset of columns than the marketing team needs access to.

Which combination of steps should the data engineer take to meet these requirements? (Select TWO.)

A.

Create views of the tables that need to be shared. Include only the required columns.

Answers
A.

Create views of the tables that need to be shared. Include only the required columns.

B.

Create an Amazon Redshift data than that includes the tables that need to be shared.

Answers
B.

Create an Amazon Redshift data than that includes the tables that need to be shared.

C.

Create an Amazon Redshift managed VPC endpoint in the marketing team's account. Grant the marketing team access to the views.

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C.

Create an Amazon Redshift managed VPC endpoint in the marketing team's account. Grant the marketing team access to the views.

D.

Share the Amazon Redshift data share to the Lake Formation catalog in the governance account.

Answers
D.

Share the Amazon Redshift data share to the Lake Formation catalog in the governance account.

E.

Share the Amazon Redshift data share to the Amazon Redshift Serverless workgroup in the marketing team's account.

Answers
E.

Share the Amazon Redshift data share to the Amazon Redshift Serverless workgroup in the marketing team's account.

Suggested answer: A, E

Explanation:

The company is using a data mesh architecture with AWS Lake Formation for governance and needs to share specific subsets of data with different teams (marketing and compliance) using Amazon Redshift Serverless.

Option A: Create views of the tables that need to be shared. Include only the required columns. Creating views in Amazon Redshift that include only the necessary columns allows for fine-grained access control. This method ensures that each team has access to only the data they are authorized to view.

Option E: Share the Amazon Redshift data share to the Amazon Redshift Serverless workgroup in the marketing team's account. Amazon Redshift data sharing enables live access to data across Redshift clusters or Serverless workgroups. By sharing data with specific workgroups, you can ensure that the marketing team and compliance team each access the relevant subset of data based on the views created.

Option B (creating a Redshift data share) is close but does not address the fine-grained column-level access.

Option C (creating a managed VPC endpoint) is unnecessary for sharing data with specific teams.

Option D (sharing with the Lake Formation catalog) is incorrect because Redshift data shares do not integrate directly with Lake Formation catalogs; they are specific to Redshift workgroups.

Amazon Redshift Data Sharing

AWS Lake Formation Documentation

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asked 29/10/2024
Emmanuel Esquivel Guzman
36 questions
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