To simplify the process of model deployment by automating the transfer of data between storage and computing resources.

To automate the ingestion, transformation, and movement of data, ensuring that the data is processed efficiently and is ready for analysis and model training.

To significantly reduce data storage costs by compressing and archiving data that is not frequently accessed.

To provide a platform for data visualization, enabling data scientists to easily explore and understand the data before model training.

Both A and B are correct, as automating data processing also indirectly simplifies model deployment by ensuring data is readily available and properly formatted.