AWS Certified Data Engineer Associate DEA-C01 Practice Question

A company ingests customer orders into an Amazon S3 data lake. Compliance rules state that the first six digits of any credit-card number must be replaced with the letter X before business analysts can query the data with Amazon Athena. The solution must run automatically every night, store the sanitized results in a separate S3 prefix, and avoid writing or maintaining custom code. Which approach meets these requirements?

  • Enable Amazon Macie sensitive data discovery on the bucket and configure Macie to automatically redact detected credit-card numbers before analysts access the data.

  • Use AWS Lake Formation column-level security to hide the credit-card column and grant analysts access to a masked view of that column.

  • Create an AWS Glue DataBrew project with a recipe that masks the first six digits of the credit-card column, then schedule a DataBrew job to write the output to a sanitized S3 prefix.

  • Configure server-side encryption with an AWS KMS key on the S3 bucket so that analysts access only encrypted objects through an S3 Access Point.

AWS Certified Data Engineer Associate DEA-C01
Data Security and Governance
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