Correct Option: D. To enable the design, management, and monitoring of ETL processes through a visual interface, facilitating data integration from various sources.

Explanation: Google Cloud Data Fusion is a fully managed, cloud-native data integration service that simplifies the creation and management of data pipelines. It provides a visual interface for designing ETL processes, making it accessible to users without deep coding expertise. This is particularly beneficial for the e-commerce platform's requirement for complex ETL processes and integration with multiple data sources.

Key features include:

• Visual interface: A drag-and-drop environment for pipeline construction.
• Pre-built connectors: Easy integration with various data sources and targets.
• Data transformation: Utilize built-in functions or custom code for data manipulation.
• Scheduling and monitoring: Tools to schedule pipelines and monitor their execution.

Why other options are incorrect:

• A. To act as a centralized data warehouse: While Data Fusion can populate data warehouses, its primary function is not to serve as a data warehouse itself.
• B. To deploy and manage machine learning models: Data Fusion focuses on data integration and pipeline construction, not on model deployment.
• C. To offer serverless computing capabilities: Although it may leverage serverless technologies, its core purpose is data integration, not providing serverless computing.
• E. Both A and D are correct: Only D is correct as Data Fusion's primary function is not to serve as a data warehouse.