DEA-C01 exam dumps

DEA-C01 practice question 75 of 550

AWS Certified Data Engineer - Associate. Associate level, Amazon Web Services. Free question with the correct answer and a full explanation.

DEA-C01 Question 75

Single answer

You are designing a data pipeline to process large volumes of semi-structured data from an e-commerce platform. The data is first ingested from multiple sources, processed in stages, and finally stored in Amazon Redshift for analytics. You want to use an intermediate data staging location to temporarily store the data between the ingestion and processing stages. Which AWS service is the most suitable and cost-effective option for this use case?

  1. A

    Amazon S3

  2. B

    Amazon RDS

  3. C

    Amazon DynamoDB

  4. D

    Amazon EBS

Show answer and explanation

Correct answer: A

Explanation

Amazon S3 is the most suitable option for intermediate data staging in this use case because it offers high scalability, durability, and cost-efficiency. It integrates seamlessly with other AWS services like AWS Glue, Amazon EMR, and Redshift, making it an ideal choice for data pipelines. Other options, such as Amazon RDS, Amazon DynamoDB, and Amazon EBS, are either not designed for temporary staging or are not cost-effective for this purpose.

  • A. Correct.

    Amazon S3 is a cost-effective, durable, and scalable storage service that is ideal for intermediate data staging in pipelines. It supports a wide range of tools for processing and analytics, making it the best choice for this use case.

  • B. Incorrect.

    Amazon RDS is a relational database service and is not designed for temporary data staging. It's better suited for structured data and transactional workloads rather than intermediate staging for pipelines.

  • C. Incorrect.

    Amazon DynamoDB is a NoSQL database optimized for low-latency operations, not for staging large volumes of semi-structured data in a pipeline. It is not a cost-effective option for this use case.

  • D. Incorrect.

    Amazon EBS provides block storage for individual EC2 instances. It is not suitable for large-scale, intermediate data staging because it lacks the scalability and cost-efficiency needed for this type of workload.

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