Data mining has become very important in the business world and will continue on this track due to the effectiveness of it. Mobile phone and utilities companies use data mining and business intelligence to predict churning, the terms they use for when a customer leaves their company to get their phone/gas/broadband from another provider. They collate billing information, customer services interactions, website visits and other metrics to give each customer a probability score, then target offers and incentives to customers whom they perceive to be at a higher risk of churning. Retailers segment customers into Recency, Frequency, Monetary (RFM) groups and target marketing and promotions to those different groups. A customer who spends little but often and last did so recently will be handled differently to a customer who spent big but only once and a while ago. Many E-commerce companies use data mining and business intelligence to offer cross-sells and up-sells through their websites. One of the most famous of these is Amazon, who use sophisticated mining techniques to drive their, People who viewed that product, also liked this functionality.Data mining applications are widely used in a variety of industries because they enable quick and relatively inexpensive analysis for massive volumes of data. This makes data mining an effective tool for a range of uses within the federal government, which applies it for analyzing intelligence to reduce the risk of terrorist attacks. Since the September 11, 2001 terrorist attacks, data mining has been increasingly employed to help detect threats to national security. By collecting and analyzing public and private sector data, government data mining is able to identify potential terrorists or other dangerous activities by unknown individuals.