AWS Certified Data Engineer Associate DEA-C01 Practice Question

A company stores clickstream events in an Amazon Redshift table that ingests millions of new rows every few minutes. Analysts need a pre-aggregated summary that is available no more than 15 minutes after data lands, and the data engineering team wants to avoid operating external ETL jobs. Which Amazon Redshift feature should the team use to meet these requirements with the least operational overhead?

  • Create a materialized view on the events table and enable AUTO REFRESH to incrementally maintain the aggregation.

  • Schedule an AWS Glue Spark job every 15 minutes to aggregate the data and insert the results back into Amazon Redshift.

  • Unload new rows to Amazon S3 on a 15-minute schedule and query the aggregated data through Amazon Redshift Spectrum external tables.

  • Define a standard view on the events table and rely on Amazon Redshift result caching for fast reads.

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