Soumen et al (2009) agree that data quantity surrounding us is humongous and the amount of information bombarding us is increasing. Making sense of this increasing data volume requires data mining skills and techniques that have evolved with increase in computing power. An allied discipline is Competitive intelligence which is a discipline used for improving market standing, improving strategic thinking – seeing through morass of disinformation and market disruptions and interpreting events without getting emotionally swayed with “pregnant” data. It is about analyzing an opportunity or threat before it has materialized (Reviews 2007).
Finding patterns in data is a common way of analysis. Scientists want to discover the pattern and use the patterns for developing theories that can be extended beyond the concerned data in allied fields. This helps the scientists predict what will happen in newer situations. Intelligence is thus about using the available information in an efficient manner based on picture which may or may not be perfectly clear and exploiting the gleaned intelligence for making strategic decisions. Data mining calls for electronic data storage and using of specified search for pattern identification. Global data doubles by in every 20 months, and increased availability of machines that can digest and process such data have increased opportunities for data mining. Intelligently analyzed data may our only redemption in making sense of the growing data volume. Bits and pieces of information lead to understanding of the big picture. Data mining is using the existing data to solve problems and discovering patterns in data. Consumer shopping data might help in eliciting likely reason for customer loyalty and churn. Also data analysis on same database may identify the reason why customer may be attracted to other product or service thus allowing development of special