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A business analyst with no coding background wants to build and deploy predictive models using a simple UI. Which SageMaker feature should they use?
A
SageMaker Ground Truth
B
SageMaker Studio
C
SageMaker Canvas
D
SageMaker Pipelines
Explanation:
SageMaker Canvas is the correct answer because it provides a visual, no-code interface specifically designed for business analysts and non-technical users to build and deploy machine learning models.
No-code interface: Provides a drag-and-drop visual interface that doesn't require programming knowledge
Targeted for business users: Specifically designed for business analysts, data analysts, and other non-technical roles
End-to-end ML workflow: Allows users to prepare data, build models, generate predictions, and deploy models without writing code
Business-friendly: Focuses on business outcomes rather than technical implementation details
A) SageMaker Ground Truth: This is for data labeling and annotation, not for building and deploying predictive models
B) SageMaker Studio: This is an integrated development environment (IDE) for data scientists and developers who write code
D) SageMaker Pipelines: This is for building ML workflows programmatically using code, not suitable for non-technical users
SageMaker Canvas democratizes machine learning by enabling business users to leverage ML capabilities without needing data science expertise or coding skills.