AWS Certified Solutions Architect – Associate (SAA-C02) — Question 658

A company has one million users that use its mobile app. The company must analyze the data usage in near-real time. The company also must encrypt the data in near-real time and must store the data in a centralized location in Apache Parquet format for further processing.
Which solution will meet these requirements with the LEAST operational overhead?

Answer options

• A. Create an Amazon Kinesis data stream to store the data in Amazon S3. Create an Amazon Kinesis Data Analytics application to analyze the data. Invoke an AWS Lambda function to send the data to the Kinesis Data Analytics application.
• B. Create an Amazon Kinesis data stream to store the data in Amazon S3. Create an Amazon EMR cluster to analyze the data. Invoke an AWS Lambda function to send the data to the EMR cluster.
• C. Create an Amazon Kinesis Data Firehose delivery stream to store the data in Amazon S3. Create an Amazon EMR cluster to analyze the data.
• D. Create an Amazon Kinesis Data Firehose delivery stream to store the data in Amazon S3. Create an Amazon Kinesis Data Analytics application to analyze the data.

Correct answer: D

Explanation

Amazon Kinesis Data Firehose can natively convert incoming data to Apache Parquet format and encrypt it before delivering it to Amazon S3, eliminating the need to manage custom transformation code. Combining this with Amazon Kinesis Data Analytics provides a completely serverless, fully managed pipeline for near-real-time ingestion and analysis. Alternatives that use Amazon EMR clusters or custom AWS Lambda functions introduce significantly higher operational overhead for cluster management and code maintenance.