What feature of the Transforms API allows you to generate multiple output datasets from a single input dataset efficiently?

The feature that enables the generation of multiple output datasets from a single input dataset efficiently is known as Multiple-output Transforms. This capability is designed to facilitate scenarios where a single transformation operation can yield different datasets based on the same initial input, allowing for a more streamlined and organized data processing workflow.

Utilizing Multiple-output Transforms enhances efficiency by reducing the need for multiple passes through the input data, thus optimizing the processing time and resources. This feature is particularly valuable in complex data workflows where different analyses or data outputs are required from a single source without the overhead of multiple, separate transformation procedures.

In contrast, other options focus on different aspects of the Transforms API. Transform logic level versioning (TLLV) pertains to versioning changes in transformation logic rather than output generation. Transform generation using for-loops involves procedural iterations but does not inherently optimize for multiple outputs in a single execution context. TransformContext injection relates to the environment and configuration within which the transforms operate, but does not directly address the capability of output generation from a single input dataset.