Data cleaning includes processes of filling missing values, correcting inconsistencies, identifying outliers and getting rid of them. Missing values can be filled with attribute mean, attribute mean of all tuples belonging to the same class of the given tuple containing missing values, overall system mean, and a prediction produced by a learning algorithm.