DEA-C01 exam dumps

DEA-C01 practice question 480 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 480

Single answer

You are working as a Data Engineer for a company that uses Amazon Redshift to store analytical data. The company requires you to load real-time streaming data from Amazon Kinesis Data Streams into Amazon Redshift for analysis. Which approach should you use to accomplish this?

  1. A

    Use AWS Glue to directly connect Amazon Kinesis Data Streams to Amazon Redshift.

  2. B

    Configure an Amazon Kinesis Data Firehose delivery stream to load data into Amazon Redshift.

  3. C

    Use Amazon Redshift Spectrum to query data directly from Amazon Kinesis Data Streams.

  4. D

    Write a custom application using the AWS SDK to stream data from Amazon Kinesis Data Streams into Amazon Redshift.

Show answer and explanation

Correct answer: B

Explanation

The best approach for loading real-time data from Amazon Kinesis Data Streams into Amazon Redshift is to use Amazon Kinesis Data Firehose. Firehose is a fully managed service that can capture, transform, and load streaming data into Amazon Redshift, S3, or Elasticsearch. This eliminates the need for complex custom applications or manual data handling processes.

  • A. Incorrect.

    AWS Glue does not provide direct integration to move real-time streaming data from Amazon Kinesis Data Streams to Amazon Redshift. It is better suited for ETL jobs involving batch processing.

  • B. Correct.

    Amazon Kinesis Data Firehose natively supports loading streaming data into Amazon Redshift. It is designed for this use case and simplifies the process.

  • C. Incorrect.

    Amazon Redshift Spectrum allows querying data stored in S3 but does not support querying real-time streaming data from Amazon Kinesis Data Streams.

  • D. Incorrect.

    While it is technically possible to write a custom application using the AWS SDK, this approach requires significant effort and lacks the efficiency and scalability of a managed service like Kinesis Data Firehose.

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