Q68 — AWS SAA-C03 Ch.15

Question 68 of 100 | ← Chapter 15

Q1168. 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?

Correct Answer: B. Use Amazon QuickSight to visualize the data. Use ML-powered forecasting in QuickSight to create forecasts.

Explanation

To meet the company's requirements of using automatic machine learning (ML) for forecasting complex scenarios and trends with the least management overhead, the best solution is:Correct Answer:BB. Use Amazon QuickSight to visualize the data. Use ML-powered forecasting in QuickSight to create forecasts.Explanation:Amazon QuickSight ML-Powered Forecasting: QuickSight includes built-in ML capabilities for forecasting trends and scenarios without requiring manual ML model development. It automatically analyzes time-series data and generates forecasts using pre-trained ML models. This is a fully managed solution with minimal setup or management overhead. Visualization in QuickSight: QuickSight can also visualize the forecasted data alongside historical data, providing a unified dashboard.Why Other Options Are Incorrect:A. Use an AWS Glue ML job to transform the data and create forecasts. Use Amazon QuickSight to visualize the data.AWS Glue is for ETL (Extract, Transform, Load) and data preparation, not for automatic ML forecasting. You would need to manually develop or integrate an ML model, increasing management overhead. C. Use a prebuilt ML AMI from the AWS Marketplace to create forecasts. Use Amazon QuickSight to visualize the data.A prebuilt ML AMI requires manual setup, configuration, and maintenance of the ML environment. This increases operational overhead compared to QuickSight's built-in ML forecasting. D. Use Amazon SageMaker AI inference pipelines to create and update forecasts. Use Amazon QuickSight to visualize the combined data.Amazon SageMaker is a powerful but complex ML service requiring model training, deployment, and pipeline management.This involves significant management overhead (e.g., model tuning, monitoring, infrastructure setup). Key Takeaways: QuickSight's ML-powered forecasting is the simplest and most managed solution for automatic forecasting.Other options require manual ML model development, deployment, or infrastructure management, increasing overhead.Final Answer:B. Use Amazon QuickSight to visualize the data. Use ML-powered forecasting in QuickSight to create forecasts.