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A company is developing a platform to process large volumes of data for complex analytics...

A company is developing a platform to process large volumes of data for complex analytics and machine learning (ML) tasks. The platform must handle compute-intensive workloads. The workloads currently require 20 to 30 minutes for each data processing step.

The company wants a solution to accelerate data processing.

Which solution will meet these requirements with the LEAST operational overhead?

A.

Deploy three Amazon EC2 instances. Distribute the EC2 instances across three Availability Zones. Use traditional batch processing techniques for data processing.

B.

Create an Amazon EMR cluster. Use managed scaling. Install Apache Spark to assist with data processing.

C.

Create an AWS Lambda function for each data processing step. Deploy an Amazon Simple Queue Service (Amazon SQS) queue to relay data between Lambda functions.

D.

Create a series of AWS Lambda functions to process the data. Use AWS Step Functions to orchestrate the Lambda functions into data processing steps.

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