In data transformation, what does the term "passive transformation" imply?

The term "passive transformation" in data integration contexts refers to processes that allow transformations to occur without altering the original data from the source. Specifically, this means that during a passive transformation, new data can be generated based on the input received, but the source data remains unchanged in its structure and content.

This characteristic is essential in various data processing scenarios where it’s important to keep the original dataset intact while creating derived datasets or additional information. For instance, when performing calculations or aggregating data, the original rows from the source are not impacted, showcasing the passive nature of the transformation.

In contrast, other options involve modifications or alterations to the original data or its structure, which falls outside the definition of passive transformation. By focusing specifically on generating new data while preserving the original, the correct answer encapsulates the essence of what passive transformation entails in data integration practices.