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A company's marketing data is uploaded from multiple sources to an Amazon S3 bucket A...

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A company's marketing data is uploaded from multiple sources to an Amazon S3 bucket A series ot data preparation jobs aggregate the data for reporting The data preparation jobs need to run at regular intervals in parallel A few jobs need to run in a specific order later

The company wants to remove the operational overhead of job error handling retry logic, and state management

Which solution will meet these requirements?

A.

Use an AWS Lambda function to process the data as soon as the data is uploaded to the S3 bucket Invoke Other Lambda functions at regularly scheduled intervals

B.

Use Amazon Athena to process the data Use Amazon EventBndge Scheduler to invoke Athena on a regular internal

C.

Use AWS Glue DataBrew to process the data Use an AWS Step Functions state machine to run the DataBrew data preparation jobs

D.

Use AWS Data Pipeline to process the data. Schedule Data Pipeline to process the data once at midnight.

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