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AWS Certified Data Engineer Associate DEA-C01 Practice Question

A retail company stores several years of analytics data in Amazon Redshift. The order-processing application writes live transactional data to an Amazon Aurora MySQL cluster. Data engineers need to let analysts run ad-hoc joins between the Aurora tables and Redshift fact tables with near-real-time results but minimal operational overhead and no recurring ETL jobs. Which solution meets these requirements?

  • Schedule nightly AWS Glue ETL jobs that export Aurora data to Amazon S3 in Parquet and COPY it into Redshift.

  • Set up AWS Database Migration Service (AWS DMS) to continuously replicate Aurora tables into a Redshift staging schema, then query the replicated data.

  • Use Amazon Redshift federated queries to create an external schema for the Aurora MySQL cluster and run joins directly from Redshift.

  • Enable Amazon Redshift Spectrum and register the Aurora tables as external tables through an AWS Glue JDBC crawler.

AWS Certified Data Engineer Associate DEA-C01
Data Store Management
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