Data mining is the work of analyzing business information in order to discover patterns and create predictive models that can validate new business insights.
Unlike data analytics, in which discovery goals are often not known or well defined at the outset, data mining efforts are usually driven by a specific absence of information that can’t be satisfied through standard data queries or reports. Data mining yields information from which predictive models can be derived and then tested, leading to a greater understanding of the marketplace.
Data mining uses a combination of human statistical skill and software that is programmed with pattern-recognition algorithms that detect anomalies. Thus, the term refers to both an information technology competency as well as a category of software technology.
The business application of data mining is broad. It can be used for everything from pharmaceutical research to modeling traffic patterns. However, a classic use case is to predict customer behaviors in order to optimize sales and marketing activities. For example, retailers often use data mining to predict what purchases their customers might make next. They can then respond with targeted promotions to elicit the sale.