AWS Certified Data Analytics – Specialty — Question 27

A company wants to use an automatic machine learning (ML) Random Cut Forest (RCF) algorithm to visualize complex real-world scenarios, such as detecting seasonality and trends, excluding outers, and imputing missing values.
The team working on this project is non-technical and is looking for an out-of-the-box solution that will require the LEAST amount of management overhead.
Which solution will meet these requirements?

Answer options

• A. Use an AWS Glue ML transform to create a forecast and then use Amazon QuickSight to visualize the data.
• B. Use Amazon QuickSight to visualize the data and then use ML-powered forecasting to forecast the key business metrics.
• C. Use a pre-build ML AMI from the AWS Marketplace to create forecasts and then use Amazon QuickSight to visualize the data.
• D. Use calculated fields to create a new forecast and then use Amazon QuickSight to visualize the data.

Correct answer: B

Explanation

Option B is correct because it directly utilizes Amazon QuickSight for visualization and incorporates ML-powered forecasting, aligning with the requirement for minimal management overhead. Options A and C introduce additional complexity by involving AWS Glue and pre-built AMIs, respectively, which may require more management. Option D relies on calculated fields, which may not provide the automated capabilities the team seeks.