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A company wants to research user turnover by analyzing the past 3 months of user activities. With millions of users, 1.5 TB of uncompressed data is generated each day. A 30-node Amazon Redshift cluster with 2.56 TB of solid state drive (SSD) storage for each node is required to meet the query performance goals. The company wants to run an additional analysis on a year’s worth of historical data to examine trends indicating which features are most popular. This analysis will be done once a week. What is the MOST cost-effective solution?
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Question 211 - DAS-C01 discussion

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A company wants to use automatic machine learning (ML) to create and visualize forecasts of complex scenarios and trends.

Which solution will meet these requirements with the LEAST management overhead?

A.
Use an AWS Glue ML job to transform the data and create forecasts. Use Amazon QuickSight to visualize the data.
Answers
A.
Use an AWS Glue ML job to transform the data and create forecasts. Use Amazon QuickSight to visualize the data.
B.
Use Amazon QuickSight to visualize the data. Use ML-powered forecasting in QuickSight to create forecasts.
Answers
B.
Use Amazon QuickSight to visualize the data. Use ML-powered forecasting in QuickSight to create forecasts.
C.
Use a prebuilt ML AMI from the AWS Marketplace to create forecasts. Use Amazon QuickSight to visualize the data.
Answers
C.
Use a prebuilt ML AMI from the AWS Marketplace to create forecasts. Use Amazon QuickSight to visualize the data.
D.
Use Amazon SageMaker inference pipelines to create and update forecasts. Use Amazon QuickSight to visualize the combined data.
Answers
D.
Use Amazon SageMaker inference pipelines to create and update forecasts. Use Amazon QuickSight to visualize the combined data.
Suggested answer: B
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asked 16/09/2024
Salvatore Buscio
28 questions
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