 IBM data mining helps you detect fraud, segment your customers, and simplify market basket analysis. The in-database mining capabilities integrate with existing systems to provide scalable, high performing predictive analysis without moving your data into proprietary data mining platforms. Modeling. The data mining process starts with historical data being gathered and put through a series of mathematical functions to derive business rules such as: "Customers buying Gouda cheese are likely to also buy mixed nuts 18% of the time." The business rules are collected together into a Model. A model can have a few rule or tens of thousands of rules. Visualization. The business rules must be analyzed and verified by a business analyst to ensure the rules are accurate. IBM offers a unique Visualization tool to assist analysts in evaluating the business rules. Read more Scoring. The verified business rules can be applied to new data to determine the appropriate predicted outcome. For example, a new bank transaction enters the system and the fraud detection rules are applied against the data. The rules will predict the probability that the record is fraudulent. This process of applying the business rules is called Scoring. Scoring in real time allows businesses to catch fraudulent records faster, segment new customers and offer them better service, and detect defects quicker. | 
