DEA-C01 exam dumps

DEA-C01 practice question 8 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 8

Select 2

You are designing a data pipeline to process streaming data from IoT devices. The data needs to be ingested in real-time, stored durably, and then processed for analytics. The processed results should be queried with low latency. Which combination of AWS services meets these requirements?

  1. A

    Amazon Kinesis Data Streams for ingestion, Amazon S3 for storage, and Amazon Athena for querying

  2. B

    Amazon Kinesis Data Streams for ingestion, Amazon DynamoDB for storage, and Amazon Elasticsearch Service (Amazon OpenSearch Service) for querying

  3. C

    Amazon Managed Streaming for Apache Kafka (MSK) for ingestion, Amazon S3 for storage, and Amazon Redshift for querying

  4. D

    Amazon Kinesis Data Streams for ingestion, Amazon S3 for storage, and Amazon Redshift for querying

  5. E

    Amazon Kinesis Data Streams for ingestion, Amazon DynamoDB for storage, and Amazon QuickSight for querying

Show answer and explanation

Correct answers: B, E

Explanation

To meet the requirements of real-time ingestion, durable storage, and low-latency querying, a combination of Amazon Kinesis Data Streams for ingestion, DynamoDB for storage, and either Amazon OpenSearch Service or Amazon QuickSight for querying is ideal. These services are designed to handle real-time data, ensure durability, and provide efficient querying capabilities.

  • A. Incorrect.

    Amazon Athena is suitable for querying data stored in Amazon S3, but it does not support low-latency analytics for real-time or near real-time queries. This option is not suitable for the requirements.

  • B. Correct.

    Amazon Kinesis Data Streams handles real-time ingestion, DynamoDB provides durable storage with low-latency access, and Amazon OpenSearch Service enables efficient querying of processed data. This option meets the requirements.

  • C. Incorrect.

    Amazon MSK and S3 are valid for ingestion and storage, but Redshift is not ideal for low-latency querying in this scenario as it is optimized for large-scale analytical processing, not real-time analytics.

  • D. Incorrect.

    This combination supports ingestion, durable storage, and analytics, but using Amazon Redshift for querying is not ideal for low-latency requirements. Redshift is better suited for batch analytics.

  • E. Correct.

    Amazon Kinesis Data Streams handles real-time ingestion, DynamoDB provides low-latency durable storage, and Amazon QuickSight can be used for visualizing low-latency query results. This option meets the requirements.

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