What requirement is essential for using the append transformation?

The requirement that input datasets must have identical structures is crucial for using the append transformation. When appending datasets, the system combines the rows from multiple datasets into a single dataset. For this operation to function correctly, each dataset must have the same schema, which includes having the same fields with compatible data types. This ensures that the data aligns correctly during the merging process and prevents inconsistencies or errors that may arise from differing structures.

If the structures differ — for instance, if one dataset has additional fields or different data types for existing fields — the append operation may not execute correctly or could lead to data integrity issues, such as data being placed in the wrong columns or dropping relevant information. Therefore, maintaining identical structures across the input datasets is essential to facilitate a seamless, accurate append transformation.