If you attempt to Union two datasets with differing field names, what will Alteryx do?

When attempting to Union two datasets with differing field names, Alteryx can perform a positional union, meaning it will align the records based on their positions in the datasets rather than matching them by field names. This allows the user to combine the data even if the column headers do not exactly match, which can be particularly useful when dealing with similar datasets that may have slight variations in naming conventions.

In a positional union, Alteryx takes the first column from the first dataset and aligns it with the first column of the second dataset, the second column with the second, and so on. This flexibility enables the integration of datasets without immediately requiring exact field matches, facilitating data analysis and workflow processes.

Other options, such as throwing an error or dropping one dataset, suggest that the process would stop, which is not the case as Alteryx is designed to be adaptive when it comes to data manipulation procedures like Union. Therefore, recognizing the capability of Alteryx to union datasets positionally highlights its functionality in handling diverse data sources effectively.