A company needs to ingest and analyze telemetry data from vehicles at scale for machine learning and reporting.
Which solution will meet these requirements?
A.
Use Amazon Timestream for LiveAnalytics to store data points. Grant Amazon SageMaker permission to access the data. Use Amazon QuickSight to visualize the data.
B.
Use Amazon DynamoDB to store data points. Use DynamoDB Connector to ingest data into Amazon EMR for processing. Use Amazon QuickSight to visualize the data.
C.
Use Amazon Neptune to store data points. Use Amazon Kinesis Data Streams to ingest data into a Lambda function for processing. Use Amazon QuickSight to visualize the data.
D.
Use Amazon Timestream for LiveAnalytics to store data points. Grant Amazon SageMaker permission to access the data. Use Amazon Athena to visualize the data.
Amazon Timestreamis purpose-built for storing and analyzing time-series data like telemetry.
Option Aleverages Timestream, SageMaker for ML, and QuickSight for visualization, meeting all requirements with minimal complexity.
Option Binvolves more complex DynamoDB-EMR integration.
Option Cuses Neptune, which is designed for graph databases, not telemetry data.
Option Dincorrectly uses Athena for visualization instead of QuickSight.
Contribute your Thoughts:
Chosen Answer:
This is a voting comment (?). You can switch to a simple comment. It is better to Upvote an existing comment if you don't have anything to add.
Submit