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Question 897 - SAA-C03 discussion

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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.

Answers
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.

Answers
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.

Answers
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.

Answers
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.

Suggested answer: A

Explanation:

Amazon Timestream is purpose-built for storing and analyzing time-series data like telemetry.

Option A leverages Timestream, SageMaker for ML, and QuickSight for visualization, meeting all requirements with minimal complexity.

Option B involves more complex DynamoDB-EMR integration.

Option C uses Neptune, which is designed for graph databases, not telemetry data.

Option D incorrectly uses Athena for visualization instead of QuickSight.

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asked 29/11/2024
Mahdi Far
32 questions
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