What happens if null values are encountered in a dataset?

In data processing within Alteryx, encountering null values is a common scenario, and the Data Cleansing Tool is specifically designed to handle such cases effectively. When null values are present in a dataset, this tool provides options to replace them with specified values or settings, which helps ensure data integrity and facilitates further analysis. For example, one might choose to replace nulls with averages, medians, or a specific constant, depending on the context of the data. This functionality is essential for making the dataset more complete and usable for downstream analytics.

While it is true that null values could be ignored by default in some operations, the Data Cleansing Tool provides a proactive approach to managing them. It allows users to choose their handling, which can ultimately lead to more accurate insights. The other options imply limitations on processing or alternative storage methods that are not relevant to the intuitive functionality of data preparation that the Data Cleansing Tool offers.