Q80 — AWS SAA-C03 Ch.14

Question 80 of 100 | ← Chapter 14

Q1080. A company has a large fleet of vehicles that are equipped with internet connectivity to send telemetry to the company.The company receives over 1 million data points every 5 minutes from the vehicles. The company uses the data in machine learning (ML) applications to predict vehicle maintenance needs and to preorder parts. The company produces visual reports based on the captured data.The company wants to migrate the telemetry ingestion, processing, and visualization workloads to AWS.Which solution will meet these requirements?

Correct Answer: A. Use Amazon Timestream for LiveAnalytics to store the data points. Grant Amazon SageMaker permission to access the data for processing. Use Amazon QuickSight to visualize the data.

Explanation

To determine the most suitable solution for migrating the telemetry ingestion, processing, and visualization workloads to AWS for a company with a large fleet of vehicles, let's evaluate each option based on the provided requirements:Requirements Recap:The company receives over 1 million data points every 5 minutes from vehicles. Data is used in machine learning (ML) applications for predictions and part preorders.Visual reports are produced based on the captured data.Option Analysis:A. Use Amazon Timestream for LiveAnalytics to store the data points. Grant Amazon SageMaker permission to access the data for processing. Use Amazon QuickSight to visualize the data.Advantages:Amazon Timestream is designed for time series data, which is ideal for telemetry from vehicles.LiveAnalytics allows for real-time querying and analysis.Amazon SageMaker is a powerful ML service that can effectively process and analyze the data. Amazon QuickSight provides a robust tool for data visualization.Suitability:This solution is tailored for handling high-frequency time series data, which aligns well with the company's telemetry requirements.It supports both real-time analytics and ML processing, as well as visualization. B. Use Amazon DynamoDB to store the data points. Use DynamoDB Connector to ingest data from DynamoDB into Amazon EMR for processing. Use Amazon QuickSight to visualize the data.Advantages:DynamoDB is a highly scalable NoSQL database.Amazon EMR provides a managed Hadoop and Spark service for big data processing.