DEA-C01 exam dumps

DEA-C01 practice question 196 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 196

Single answer

You are working as a Data Engineer for a company that collects IoT sensor data from devices deployed worldwide. The data is ingested into an Amazon Kinesis Data Stream and needs to be processed in near real-time to detect anomalies. The processed data should then be stored in Amazon S3 for further analysis. Which service would be the best choice for implementing the real-time anomaly detection logic?

  1. A

    Amazon Kinesis Data Analytics

  2. B

    AWS Glue

  3. C

    Amazon EMR

  4. D

    Amazon QuickSight

Show answer and explanation

Correct answer: A

Explanation

Amazon Kinesis Data Analytics is the ideal service for real-time anomaly detection in this scenario because it integrates seamlessly with Amazon Kinesis Data Streams and supports SQL-based and Apache Flink-based real-time processing. It is purpose-built for scenarios requiring near real-time data analysis, making it the best fit for the requirements described.

  • A. Correct.

    Amazon Kinesis Data Analytics is designed specifically for real-time data processing and analysis. It can consume data from a Kinesis Data Stream, execute SQL-based or Apache Flink-based anomaly detection logic in real time, and then output the results to downstream destinations such as Amazon S3.

  • B. Incorrect.

    AWS Glue is primarily a serverless ETL (Extract, Transform, Load) service that is optimized for batch data processing rather than near real-time data processing.

  • C. Incorrect.

    Amazon EMR is a big data processing service optimized for running large-scale distributed data processing frameworks like Apache Hadoop and Spark. It is more suited for batch or complex processing rather than real-time anomaly detection.

  • D. Incorrect.

    Amazon QuickSight is a business intelligence tool used for visualizing and analyzing data. It is not designed for real-time data processing or anomaly detection.

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