Crucial Exams

AWS Certified Data Engineer Associate DEA-C01 Practice Question

A data engineer needs to let business analysts visually build and test data transformations on a 5 GB sample of CSV files stored in Amazon S3, then run those same transformations every night on 2 TB of new data and write the output to Parquet for Amazon Athena. The company does not want to manage clusters or write code. Which approach meets these requirements with the least operational effort and cost?

  • Schedule an AWS Lambda function with Amazon EventBridge that runs an Amazon Athena CTAS query to convert the CSV files to Parquet each night.

  • Author a visual ETL job in AWS Glue Studio that uses Apache Spark to convert the data and trigger it nightly with a Glue workflow.

  • Create an AWS Glue DataBrew project to build a transformation recipe on the sample data and schedule a DataBrew job to run nightly on the full S3 dataset, outputting Parquet.

  • Launch an Amazon EMR cluster running Apache Spark, store the transformation script in Amazon S3, and invoke it nightly with Amazon EventBridge.

AWS Certified Data Engineer Associate DEA-C01
Data Operations and Support
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