What does the append transformation do in data preparation?

The append transformation plays a crucial role in data preparation by allowing the combination of data from different sources or streams. Specifically, it functions by adding the rows from one dataset to the rows of another dataset vertically. This means that all the entries from one stream are included as additional rows in the target dataset, effectively increasing the total number of observations available for analysis.

This transformation is especially useful when dealing with datasets that contain similar types of records but are stored separately. For instance, if data is collected from different branches of a business over similar time periods, appending these datasets will create a comprehensive view that encompasses information from all branches.

The result is a combined dataset where the original datasets retain their structure but come together to facilitate more inclusive analysis. In contrast, merging datasets based on a key, aggregating data, or filtering rows serve different purposes in the data processing workflow, focusing on combining, summarizing, or reducing the data instead of merely appending rows.