AWS Certified Data Engineer – Associate (DEA-C01) — Question 202

A retail company stores order information in an Amazon Aurora table named Orders. The company needs to create operational reports from the Orders table with minimal latency. The Orders table contains billions of rows, and over 100,000 transactions can occur each second.

A marketing team needs to join the Orders data with an Amazon Redshift table named Campaigns in the marketing team's data warehouse. The operational Aurora database must not be affected.

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

Answer options

• A. Use AWS Database Migration Service (AWS DMS) Serverless to replicate the Orders table to Amazon Redshift. Create a materialized view in Amazon Redshift to join with the Campaigns table.
• B. Use the Aurora zero-ETL integration with Amazon Redshift to replicate the Orders table. Create a materialized view in Amazon Redshift to join with the Campaigns table.
• C. Use AWS Glue to replicate the Orders table to Amazon Redshift. Create a materialized view in Amazon Redshift to join with the Campaigns table.
• D. Use federated queries to query the Orders table directly from Aurora. Create a materialized view in Amazon Redshift to join with the Campaigns table.

Correct answer: B

Explanation

The correct answer is B because the Aurora zero-ETL integration with Amazon Redshift allows for real-time replication of data without impacting the operational database, making it efficient and requiring minimal operational effort. Options A, C, and D involve more complexity and potential latency, as they require additional services or querying methods that could affect performance.