In Foundry Aware, how does a Foundry dataset differ from a dataset view?

• A. A Foundry dataset is a stored, versioned data asset that physically holds data; a dataset view is a curated, derived representation of that data used for consumption.
• B. A Foundry dataset is computed on demand, while a dataset view persists data.
• C. A Foundry dataset is only used for streaming data, while a dataset view is for batch data.
• D. A dataset view stores data in a separate lake, while a dataset stores data in memory.

Answer: (A)

Foundry distinguishes the actual data store from how that data is presented to users. A dataset is a stored, versioned asset that physically holds the data and tracks its changes over time. A dataset view, on the other hand, is a curated, derived representation built on top of that dataset for consumption. It defines how the data should look for analysts or applications—through transformations, filters, and selections—without duplicating the underlying data. The view can be computed when needed or materialized, but the underlying data remains in the dataset. This separation makes the dataset the true data store, while the dataset view serves as a consumption-ready representation.