AWS Certified Data Engineer Associate DEA-C01 Practice Question

An e-commerce company stores daily Parquet files of order events in Amazon S3, partitioned by dt=YYYY-MM-DD. A data engineer must deliver a daily report that shows the 7-day moving average of sales per product and allow analysts to perform ad-hoc joins with other S3 datasets from Amazon QuickSight. The solution must minimize infrastructure management and keep costs low. Which architecture meets these requirements?

Create an AWS Glue ETL job that loads the data into a provisioned Amazon Redshift cluster each night. Build a materialized view for the moving average and point QuickSight to the Redshift database.
Launch an Amazon EMR cluster running Apache Spark SQL on a daily schedule to compute the moving average, write the results back to S3, and expose the data to analysts through an Athena Federated Query connector to EMR.
Use AWS Glue crawler to catalog the S3 folder, query the data with Amazon Athena, and create a SQL view that uses window functions to calculate the 7-day moving average. Grant QuickSight access to Athena and schedule the query daily with Amazon EventBridge.
Create an AWS Glue DataBrew project to compute the moving average, export the output to Amazon OpenSearch Service, and connect QuickSight to OpenSearch for dashboards.

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Answer Description

Amazon Athena is a serverless query service that can read Parquet data directly from Amazon S3, supports SQL window functions for rolling calculations, and integrates natively with QuickSight without provisioning or managing infrastructure. Creating a Glue crawler registers the table in the Data Catalog so the data is discoverable. A view in Athena can encapsulate the 7-day moving average logic, and an EventBridge rule can trigger the query on a schedule if the results need to be written back to S3. Redshift and EMR require clusters to be launched, sized, patched, and paid for when idle, increasing operational effort and cost. DataBrew can produce aggregates but would still need an additional service to support ad-hoc SQL joins and is not optimized for near-real-time dashboards.

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