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AWS Certified Data Engineer Associate DEA-C01 Practice Question

A company stores weekly sales CSV files in an Amazon S3 bucket named s3://raw-sales. A business analyst must prepare the data for reporting without writing code, apply the same transformations every week, and must not be able to overwrite the raw files. As the data engineer, which solution most closely follows AWS best practices?

  • Import the CSV files into Amazon QuickSight SPICE, enable QuickSight data preparation to clean the data, and refresh the dataset on a weekly schedule.

  • Create an AWS Glue DataBrew project that reads from s3://raw-sales, let the analyst build a recipe, then configure a DataBrew job to write the output to s3://curated-sales. Attach an IAM policy that allows s3:GetObject on s3://raw-sales and s3:PutObject on s3://curated-sales only.

  • Create an Amazon Athena scheduled query that runs weekly and stores the query results in s3://curated-sales. Grant the analyst permissions to edit the SQL in the Athena console.

  • Author an AWS Glue PySpark job in AWS Glue Studio to read from s3://raw-sales and write to s3://curated-sales, then trigger it weekly with Amazon EventBridge.

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