Crucial Exams

AWS Certified Data Engineer Associate DEA-C01 Practice Question

A data analyst ingests daily CSV files into Amazon QuickSight by using an Athena data source. Some rows arrive with a null value in the customer_email column. Management requires that visualizations and calculated metrics in QuickSight never include rows that have a missing customer_email, but the underlying Athena table must remain unchanged. Which approach satisfies the requirement while ensuring that future ingestions are automatically cleaned?

  • Create an Athena view that filters out null customer_email values and point the QuickSight dataset to the view.

  • Add a filter in the QuickSight dataset editor that excludes rows where customer_email is null, then re-ingest the dataset.

  • Create a calculated field that replaces null customer_email values with the string Unknown and use that field in all visuals.

  • Define a filter inside each QuickSight analysis to hide rows with blank customer_email values.

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