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AWS Certified Data Engineer Associate DEA-C01 Practice Question

An analytics team receives hourly CSV files from external vendors. When a file lands in an S3 bucket, it must be validated, transformed with AWS Glue, and loaded into Amazon Redshift. The solution must be serverless, event-driven, include retry logic, and minimize operational overhead. Which architecture best meets these requirements?

  • Create a CloudWatch Events scheduled rule that runs every 5 minutes and invokes a Lambda function. The function lists recently added objects, kicks off an AWS Batch job to transform the data, and then loads the results into Redshift.

  • Deploy Apache Airflow on an EC2 Auto Scaling group and build a DAG that polls the S3 bucket every minute, then starts a Glue job and a Redshift COPY task.

  • Configure an S3 Event Notification to deliver ObjectCreated events to EventBridge, which triggers a Step Functions state machine. The state machine runs a Glue job for transformation, then uses the Redshift Data API to issue a COPY command. Step Functions built-in retries handle transient failures.

  • Set up Kinesis Data Firehose with the S3 bucket as the data source, enable transformation with a Lambda function, and configure the delivery stream to load directly into Amazon Redshift.

AWS Certified Data Engineer Associate DEA-C01
Data Ingestion and Transformation
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