Pharmaceutical data analytics has been defined as the process of extracting meaning from large data sets in order to improve decision making. Pharmaceutical data analytics is used in many different fields, including drug discovery, clinical trials, and patient care.

Pharmaceutical data analytics can be divided into three main categories: cleansing, exploration, and exploitation. Cleansing is the process of removing extraneous information from the data set. Exploring is the process of looking for patterns in the data set, and exploiting is the process of using the patterns found to make better decisions.