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AWS Certified Data Engineer Associate DEA-C01 Practice Question

An e-commerce company's CloudTrail logs from multiple accounts are centralized in Amazon S3 at s3://audit-logs/AWSLogs/AccountID/CloudTrail/us-east-1/YYYY/MM/DD/. A Glue table named cloudtrail_logs is queried in Athena for the last 7 days, but each query still scans several terabytes because new partitions are only added by a nightly Glue crawler. Without moving or transforming the data, which action most effectively reduces query cost and latency?

  • Create an Amazon Redshift external schema and copy the CloudTrail data into a Redshift table with sort keys on eventTime for faster SQL queries.

  • Run an AWS Glue ETL job that converts the CloudTrail JSON files to compressed Parquet under a new S3 prefix and update analysts to query the new table.

  • Enable partition projection on the Glue table and define year, month, and day ranges so Athena automatically discovers new partitions at query time.

  • Stream CloudTrail events to CloudWatch Logs and instruct analysts to run their compliance queries with CloudWatch Logs Insights instead of Athena.

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