AWS Certified Machine Learning Engineer – Associate (MLA-C01) — Question 123

A company wants to build a real-time analytics application that uses streaming data from social media. An ML engineer must implement a solution that ingests and transforms 5 GB of data each minute. The solution also must load the data into a data store that supports fast queries for the real-time analytics.

Which solution will meet these requirements?

Answer options

• A. Use Amazon EventBridge to ingest the social media data. Use AWS Glue to transform the data. Store the transformed data in Amazon ElastiCache (Memcached).
• B. Use Amazon Simple Queue Service (Amazon SQS) to ingest the social media data. Use AWS Lambda to transform the data. Store the transformed data in Amazon S3.
• C. Use Amazon Simple Notification Service (Amazon SNS) to ingest the social media data. Use Amazon EMR to transform the data. Store the transformed data in Amazon RDS.
• D. Use Amazon Kinesis Data Streams to ingest the social media data. Use Amazon Managed Service for Apache Flink to transform the data. Store the transformed data in Amazon DynamoDB.

Correct answer: D

Explanation

Option D is correct because Amazon Kinesis Data Streams can handle high throughput for streaming data, and Amazon Managed Service for Apache Flink provides powerful real-time data processing capabilities. Additionally, Amazon DynamoDB is optimized for fast querying, making it suitable for real-time analytics. The other options either do not support the required data ingestion rates or do not provide the necessary speed for querying.