Answer: Amazon SageMaker Feature Store

**Amazon SageMaker Feature Store** is the correct answer because it is specifically designed to store, share, and manage features (variables) for machine learning models across multiple teams. **Key reasons why Feature Store meets the requirements:** 1. **Feature Sharing**: Allows multiple teams to access and reuse the same features, promoting consistency and collaboration 2. **Feature Management**: Provides versioning, discovery, and governance capabilities for features 3. **Centralized Repository**: Creates a single source of truth for features used across different models and projects 4. **Real-time and Batch Features**: Supports both online (real-time) and offline (batch) feature serving **Why other options are incorrect:** - **Amazon SageMaker Data Wrangler**: Used for data preparation and feature engineering, but not specifically for sharing and managing features across teams - **Amazon SageMaker Clarify**: Used for model explainability and bias detection, not for feature management - **Amazon SageMaker Model Cards**: Used for documenting model information and metadata, not for feature management **Use Case**: When multiple teams are working on different ML models that use the same features, Feature Store ensures consistency, reduces redundant work, and maintains feature lineage.

Author: Ritesh Yadav