DEA-C01 exam dumps

DEA-C01 practice question 537 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 537

Select 2

You are designing a data pipeline to process and analyze clickstream data in real-time using AWS services. The pipeline needs to ingest streaming data, process it for aggregations, and store the results in a queryable format with low-latency access. Which combination of AWS services would best meet these requirements?

  1. A

    Amazon Kinesis Data Streams for ingestion, AWS Lambda for processing, and Amazon S3 for storage

  2. B

    Amazon Kinesis Data Firehose for ingestion, AWS Glue for processing, and Amazon Redshift for storage

  3. C

    Amazon Kinesis Data Streams for ingestion, Amazon Kinesis Data Analytics for processing, and Amazon DynamoDB for storage

  4. D

    Amazon SQS for ingestion, AWS Lambda for processing, and Amazon RDS for storage

  5. E

    Amazon Kinesis Data Streams for ingestion, AWS Lambda for processing, and Amazon Elasticsearch Service (OpenSearch) for storage

Show answer and explanation

Correct answers: C, E

Explanation

For real-time processing of streaming data, Amazon Kinesis Data Streams is the optimal service for ingestion. Amazon Kinesis Data Analytics provides the ability to process and aggregate the data on-the-fly. Amazon DynamoDB or Amazon Elasticsearch Service (OpenSearch) offer low-latency storage and querying capabilities, making them suitable for storing and querying analytics results in real-time.

  • A. Incorrect.

    Amazon Kinesis Data Streams, AWS Lambda, and Amazon S3 are a valid combination for simple data pipelines, but S3 is not optimized for low-latency querying of real-time analytics data.

  • B. Incorrect.

    Amazon Kinesis Data Firehose, AWS Glue, and Amazon Redshift are great for batch processing and analytics, but Firehose is not ideal for real-time streaming ingestion.

  • C. Correct.

    Amazon Kinesis Data Streams, Amazon Kinesis Data Analytics, and Amazon DynamoDB are a strong combination for real-time ingestion, on-the-fly processing, and low-latency storage of analytics results.

  • D. Incorrect.

    Amazon SQS is not designed for high-throughput data streaming like Amazon Kinesis Data Streams, making this combination unsuitable for the use case.

  • E. Correct.

    Amazon Kinesis Data Streams, AWS Lambda, and Amazon Elasticsearch Service (OpenSearch) are a good combination for real-time ingestion, processing, and querying of analytics data with low-latency access.

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