Data cleansing

Data cleansing is about ensuring that the data is correct and precise. This can be achieved by verifying if the data meets certain rules, discarding or correcting those which don't follow the expected pattern, setting default values for missing data, eliminating information that is duplicated, normalizing data to conform to minimum and maximum values, and so on. These are tasks that Kettle makes possible, thanks to its vast set of transformation and validation capabilities.