IntroductionThe field of business analytics has improved significantly over the last few years, providing business users with better insights, particularly from operational data stored in transactional systems. As an illustrative example, analysis of e-commerce data has recently come to be considered a killer-app for data mining [1,2]. The data sets created by integrating clickstream records generated by web sites with demographic and other behavioral data dwarf, in size and complexity, the largest data warehouses of a few years ago [3], creating massive databases that require a mix of automated analysis techniques and human effort in order to provide business users with critical insight about the activity on the site and the characteristics of the site's visitors and customers. With many millions of clickstream records being generated on a daily basis and aggregated to records with hundreds of attributes, there is a clear need for automated techniques to find patterns in the data. In this paper we discuss the technology and enterprise-adoption trends in the area of business analytics.

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