Featureform allows data scientists to define their model's features, labels, and training sets in their logical representations. In reality, the logical definitions are split across different real components: the data source, the transformations, the inference store, the training store, and all their underlying data infrastructure. Featureform then coordinates a set of infrastructure providers to make the real components match each resource's logical representation.