Data Mining and Business Intelligence-A Guide To Productivity

Data Mining and Business Intelligence: A Guide to Productivity provides an overview of data mining technology and how it is applied in a business environment. It describes the corresponding data mining methodologies that are used to solve a variety of business problems which enhance firm-level efficiency in a less technical, more managerial style. The book incorporates the data mining process into the spectrum of complementary technologies that together comprise corporate information systems that promote business intelligence. Business intelligence involves the proliferation of value-added information throughout a given enterprise through the use of various applications that promotes efficiency for the firm.

Richard Hoptroff obtained a PhD in Physics in London for developing optimization algorithms and neural networks for industrial applications including control systems and robot vision. After graduating in 1992, he applied the same techniques to economics and business modeling. After initially working as a consultant, he started Right Information Systems (RIS), a software company dedicated to producing what was to become known as data mining software. RIS's premier product was 4Thought, a neural-network based modeling and forecasting package. In 1997, RIS was acquired by Cognos Inc of Ottawa, Canada, where he became Director of Data Mining. In 1999 he returned to independent consulting and is currently based in Amsterdam in the Netherlands.Stephan Kudyba (PhD) is president and founder of Null Sigma Inc., a consulting company that concentrates on enhancing corporate operational efficiency through the utilization of data mining, business intelligence and knowledge management initiatives. He is also a faculty member in the school of management at New Jersey Institute of Technology and has authored the books Data Mining and Business Intelligence: A Guide to Productivity and IT, Corporate Productivity and the New Economy.