Data mining by business users
Marcel Holsheimer · 1999
Data mining is often performed on an ad-hoc basis where fairly complex business problems are analyzed.However, we believe that the greater value of data mining is not in such complex analysis by statisticians or data mining experts, but in a day to day use of data mining as part of a company's primary processes.These so-called data mining solutions will be used by business users, such as marketeers, rather than by statisticians.Data Distilleries has gained considerable experience in implementing data mining solutions, based on the European KESO research framework.This technology is used by leading banks and insurance companies as integrated part of their marketing and sales processes.From these experiences, new research directions arise, such as "how can the quality of mining results be guaranteed when non-experts are using technology?"and "how can the results of data mining be integrated in business processes?".In this tutorial, we will go in depth into our experiences and outline which new research directions arise from these experiences.We hope that the combination of our scientific background and our practical experiences will help the research community in exploring even more challenging areas. About the Tutor.Marcel Holsheimer is CEO and founder of Data Distilleries.Marcel started his academic career at CWI, the Dutch research center for mathematics and computer science, working on data mining research.After having several successful publications at the early KDD conferences, he decided to start his own company Data Distilleries.Based on this research, Data Distilleries offers a suite of data mining solutions for Customer Relationship Management and an analysis and development environment for data mining solutions.These solutions are used on European wide scale at leading banks and insurance companies.Data Distilleries is regarded as one of the promising European companies to bring data mining solutions to a wide scale use in business environments.Moreover, Data Distilleries is an example of a successful spin off of a research institute and proves that data mining cannot only be challenging from a research point of view, but also of great value in commercial situations.