AWS Certified Data Analytics – Specialty — Question 136

A media company has a streaming playback application. The company needs to collect and analyze data to provide near-real-time feedback on playback issues within 30 seconds. The company requires a consumer application to identify playback issues, such as decreased quality during a specified time frame. The data will be streamed in JSON format. The schema can change over time.
Which solution will meet these requirements?

Answer options

• A. Send the data to Amazon Kinesis Data Firehose with delivery to Amazon S3. Configure an S3 event to invoke an AWS Lambda function to process and analyze the data.
• B. Send the data to Amazon Managed Streaming for Apache Kafka. Configure Amazon Kinesis Data Analytics for SQL Application as the consumer application to process and analyze the data.
• C. Send the data to Amazon Kinesis Data Firehose with delivery to Amazon S3. Configure Amazon S3 to initiate an event for AWS Lambda to process and analyze the data.
• D. Send the data to Amazon Kinesis Data Streams. Configure an Amazon Kinesis Data Analytics for Apache Flink application as the consumer application to process and analyze the data.

Correct answer: D

Explanation

The correct answer is D because Amazon Kinesis Data Streams allows for real-time data processing which is essential for identifying playback issues within the required 30 seconds. Option A sends data to S3, which introduces latency and is not suitable for near-real-time analysis. Option B uses Apache Kafka, which is not as straightforward for real-time analytics compared to Kinesis. Option C also relies on S3, leading to delays in data processing.