Crucial Exams

AWS Certified Data Engineer Associate DEA-C01 Practice Question

An e-commerce company lands raw clickstream JSON files in an S3 bucket every day. Analysts query the files with Amazon Athena, but many queries fail because some events lack required keys and several date fields use multiple formats. The data should be cleansed once so future Athena queries run without additional filters, and the solution should use managed, serverless services with minimal code. Which approach meets these requirements MOST effectively?

  • COPY the raw data into an Amazon Redshift table with MAXERROR allowed and clean the data with SQL before creating external tables for Athena.

  • Load the raw files into Amazon QuickSight Spice and use calculated fields to fix bad dates before every dashboard refresh.

  • Create an AWS Glue ETL job that drops malformed records and standardizes the date field, then writes the results to a partitioned curated S3 prefix queried by Athena.

  • Define an Athena view that converts the date on the fly and filters out rows where the required key is null.

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