Bringing automated means into the discovery of trends, patterns and relationships in data. Employing statistical or AI techniques to find hidden nuggets of knowledge that may not be immediately visibility or counterintuitive. Data mining can uncover associations (correlations between events), sequences (events leading to other events), classifications (patterns to establish profiles), clustering (finding and visualizing new groups of facts), and forecasting (discovering patterns that lead to predictions about the future).
With both reporting and OLAP solutions, business users apply their understanding of the business to analyze and present information. Where business rules may not be clear (for example, the rules predicting customer behavior or fraud) data mining technologies are used to help derive predictive rules from patterns in historic data. These rules can then be used to segment and categories new data - for example, to target profitable or at-risk customers, or potentially fraudulent credit card transactions.