Crucial Exams

AWS Certified Data Engineer Associate DEA-C01 Practice Question

A data engineer needs to automate validation of sensor data that lands as CSV files in an S3 bucket. The temperature column must contain numeric values between -50 and 180 °F; any rows outside this range should be isolated for later inspection. The solution must be serverless, require minimal custom code, and run as part of the daily ingestion pipeline before downstream analytics in Amazon Athena. Which approach best meets these requirements while ensuring data accuracy?

  • Require analysts to include a CASE expression in every Athena query that filters out temperature values below -50 or above 180 °F.

  • Load the files into Amazon Redshift and define a CHECK constraint on the temperature column so COPY rejects any out-of-range rows.

  • Enable Amazon S3 Object Lock on the landing bucket to block uploads containing temperature values outside the accepted range.

  • Create an AWS Glue DataBrew profile and recipe with a numeric range rule for the temperature column, then schedule the DataBrew job to export invalid rows to a quarantine S3 prefix.

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