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AWS Certified Data Engineer Associate DEA-C01 Practice Question

An e-commerce company stores daily CSV sales files in an S3 prefix partitioned by year, month, and day. Business analysts query the data with Amazon Athena minutes after each file lands. The data engineering team must keep the AWS Glue Data Catalog current, detect new partitions automatically, and label columns that contain customer PII for Lake Formation permissions with minimal ongoing maintenance. Which approach best meets these requirements?

  • Launch an Amazon EMR cluster on a cron schedule to import the Glue catalog into Hive and replicate it to an on-premises MySQL database; manage PII access with SQL GRANT statements.

  • Define the table in an AWS CloudFormation stack and update the stack daily with new partitions; mark PII by tagging the underlying S3 objects.

  • Configure an AWS Glue crawler that is triggered by Amazon S3 event notifications; allow the crawler to infer the schema and partitions, then apply Lake Formation column tags to the sensitive columns.

  • Run a scheduled AWS Glue ETL job each day that issues ALTER TABLE ADD PARTITION statements in Athena and maintains PII information in a separate spreadsheet.

AWS Certified Data Engineer Associate DEA-C01
Data Store Management
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