MLS-C01 Question #273: Real Exam Question with Answer & Explanation

Question

Each morning, a data scientist at a rental car company creates insights about the previous day's rental car reservation demands. The company needs to automate this process by streaming the data to Amazon S3 in near real time. The solution must detect high-demand rental cars at each of the company's locations. The solution also must create a visualization dashboard that automatically refreshes with the most recent data. Which solution will meet these requirements with the LEAST development time?

Options

• AUse Amazon Kinesis Data Firehose to stream the reservation data directly to Amazon S3. Detect
• BUse Amazon Kinesis Data Streams to stream the reservation data directly to Amazon S3. Detect
• CUse Amazon Kinesis Data Firehose to stream the reservation data directly to Amazon S3. Detect
• DUse Amazon Kinesis Data Streams to stream the reservation data directly to Amazon S3. Detect

Explanation

The company needs to stream reservation data to S3, detect high-demand cars, and visualize the data in a dashboard with minimal development time.

Common mistakes.

• B. Amazon Kinesis Data Streams requires more development effort to manage shards and consumer applications compared to Kinesis Data Firehose for simple data delivery to S3.
• C. While Kinesis Data Firehose to S3 is efficient, using an AWS Lambda function to detect high demand adds more development time for writing and managing custom code compared to using a serverless query service like Amazon Athena for immediate analysis.
• D. Amazon Kinesis Data Streams requires more development effort to manage shards and consumer applications compared to Kinesis Data Firehose for simple data delivery to S3.

Concept tested. Real-time data streaming, serverless analytics, low-code visualization

Reference. https://docs.aws.amazon.com/firehose/latest/dev/what-is-this-service.html

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