MLA-C01 exam dumps

MLA-C01 practice question 36 of 458

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

MLA-C01 Question 36

Select 1

A machine learning team is building a recommendation system that needs to process large volumes of clickstream data in near real-time. They also need to store this data for long-term analysis and model retraining. Which AWS storage options should they use to efficiently meet these requirements?

  1. A

    Amazon S3 for long-term storage and Amazon Kinesis Data Streams for real-time ingestion

  2. B

    Amazon EBS for real-time ingestion and Amazon S3 for long-term storage

  3. C

    Amazon DynamoDB for real-time ingestion and Amazon S3 Glacier for long-term storage

  4. D

    Amazon Redshift for real-time ingestion and Amazon S3 for long-term storage

  5. E

    Amazon S3 for both real-time ingestion and long-term storage

Show answer and explanation

Correct answer: A

Explanation

The combination of Amazon S3 and Amazon Kinesis Data Streams is the best choice for this use case. Kinesis Data Streams is specifically designed for ingesting and processing real-time data streams, while Amazon S3 provides highly durable and cost-effective storage for long-term data retention and analysis. Other options either do not support real-time ingestion or are not suitable for long-term storage in the context of the described requirements.

  • A. Correct.

    Amazon S3 is ideal for long-term storage due to its durability and scalability. Amazon Kinesis Data Streams is designed for real-time data processing, making this combination suitable for the described use case.

  • B. Incorrect.

    Amazon EBS is primarily used for block storage attached to EC2 instances and is not designed for real-time ingestion. While Amazon S3 is suitable for long-term storage, EBS does not meet the requirements for this scenario.

  • C. Incorrect.

    Amazon DynamoDB is a NoSQL database service designed for key-value and document storage, not for real-time ingestion of streaming data. Amazon S3 Glacier is optimized for archival storage, not active long-term storage needed for retraining.

  • D. Incorrect.

    Amazon Redshift is a data warehouse solution designed for querying and analytics, not real-time ingestion. While Amazon S3 is a good choice for long-term storage, Redshift does not meet the real-time ingestion requirement.

  • E. Incorrect.

    Amazon S3 is highly scalable but not designed for real-time ingestion of streaming data. While it is ideal for long-term storage, it cannot handle the real-time processing needs described in the scenario.

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