What is a principal characteristic of the ‘union’ operation in data processing?

The principal characteristic of the 'union' operation in data processing is that it appends similar fields from different datasets into a singular dataset. This operation is primarily used to combine records from two or more datasets that share a similar structure. In the context of data processing, the datasets being combined must have the same number of fields and compatible data types for each field to ensure that the resulting dataset maintains data integrity.

This operation is particularly useful when you want to consolidate information from various sources that contain related data. It ensures that all the relevant entries are captured in a unified view, enhancing the ability to analyze or report on that aggregated information.

The other choices do not accurately describe the union operation. While a requirement for common fields (first choice) is indeed necessary, it doesn’t define the unique function of the union itself. The union does not limit itself to numeric datasets since it can be applied across various data types. Lastly, embedding files from different sources while maintaining separation (fourth choice) describes a different operation, such as a join or a merge, rather than a union, which focuses on combining datasets into one cohesive output.