Q88 — AWS AIF-C01 Ch.1

Question 88 of 100 | ← Chapter 1

A digital device company wants to forecast customer demand for memory hardware. The company lacks coding experience or machine learning expertise and needs to develop a data-driven forecasting model. It must analyze both internal and external data. Which solution meets these requirements?

• A. Store data in Amazon S3. Use Amazon SageMaker built-in algorithms with data from Amazon S3 to build a machine learning model and perform demand forecasting.
• B. Import data into Amazon SageMaker Data Wrangler. Use SageMaker built-in algorithms to build a machine learning model and perform demand forecasting.
• C. Import data into Amazon SageMaker Data Wrangler. Use the Amazon Personalize Trending-Now template to build a machine learning model and perform demand forecasting.
• D. Import data into Amazon SageMaker Canvas. Build a machine learning model and perform demand forecasting by selecting values from the data within SageMaker Canvas. ✓

Correct Answer: D. Import data into Amazon SageMaker Canvas. Build a machine learning model and perform demand forecasting by selecting values from the data within SageMaker Canvas.

Explanation

Amazon SageMaker offers multiple tools for building ML models without requiring coding or deep ML expertise. Amazon SageMaker Canvas is a visual, no-code interface enabling users to select data sources, prepare data, train models, and generate predictions via point-and-click operations—ideal for non-technical users seeking data-driven decision-making capabilities.