Data discretization is the process of converting continuous data into discrete buckets or intervals, which can simplify data analysis and improve the performance of machine learning algorithms by reducing noise and computational complexity. It is essential in scenarios where data needs to be categorized or when certain models require discrete input, such as decision trees or rule-based classifiers.