AWS Certified Data Engineer – Associate (DEA-C01) — Question 107

A retail company stores data from a product lifecycle management (PLM) application in an on-premises MySQL database. The PLM application frequently updates the database when transactions occur.

The company wants to gather insights from the PLM application in near real time. The company wants to integrate the insights with other business datasets and to analyze the combined dataset by using an Amazon Redshift data warehouse.

The company has already established an AWS Direct Connect connection between the on-premises infrastructure and AWS.

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

Answer options

• A. Run a scheduled AWS Glue extract, transform, and load (ETL) job to get the MySQL database updates by using a Java Database Connectivity (JDBC) connection. Set Amazon Redshift as the destination for the ETL job.
• B. Run a full load plus CDC task in AWS Database Migration Service (AWS DMS) to continuously replicate the MySQL database changes. Set Amazon Redshift as the destination for the task.
• C. Use the Amazon AppFlow SDK to build a custom connector for the MySQL database to continuously replicate the database changes. Set Amazon Redshift as the destination for the connector.
• D. Run scheduled AWS DataSync tasks to synchronize data from the MySQL database. Set Amazon Redshift as the destination for the tasks.

Correct answer: B

Explanation

The correct answer is B because AWS DMS is specifically designed for database replication and can handle change data capture (CDC) efficiently, allowing near real-time updates with minimal development effort. Option A requires more effort in setting up and managing an ETL job, while C involves custom development for a connector, which increases complexity. Option D is not suitable for real-time updates as it focuses on scheduled synchronization.