What happens if multiple files have schemas that are too different when importing?

When importing multiple files with schemas that are significantly different, the process typically results in the failure to import any dataset at all. This occurs because data tools require a consistent structure across datasets to effectively handle and integrate the incoming data. If the schemas vary widely—such as mismatched column names, data types, or the number of columns—this inconsistency prevents the system from consolidating the files into a unified dataset. Therefore, without a compatible schema, the import operation is unable to proceed, leading to the conclusion that no dataset will be imported.

This outcome differs from options that suggest partial outcomes like importing the first file only or creating a blank dataset, which would imply that some processing could still occur despite the differences. Similarly, while alerts and warnings might be useful in other contexts, they would not facilitate successful imports in this scenario where schemas are too divergent.