AWS Certified Data Engineer - Associate DEA-C01 — Topic 1 Question 17

Question

A data engineer is building a data pipeline on AWS by using AWS Glue extract, transform, and load (ETL) jobs. The data engineer needs to process data from Amazon RDS and MongoDB, perform transformations, and load the transformed data into Amazon Redshift for analytics. The data updates must occur every hour. Which combination of tasks will meet these requirements with the LEAST operational overhead? (Choose two.)

Accepted Answer

Correct answer: A, D. The correct answer is A, D. Option A: Configure AWS Glue triggers to run the ETL jobs every hour. Option D: Use AWS Glue connections to establish connectivity between the data sources and Amazon Redshift. Amazon Redshift is a managed petabyte-scale data warehouse for complex analytical queries. AWS Glue is a serverless ETL and data-catalog service that prepares and integrates data. AWS Config tracks resource configuration changes and evaluates compliance.

AWS Certified Data Engineer - Associate DEA-C01 — Question 17