Translating Advances in Data Mining in Business Operations: The Art of Data Mining in Retailing

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Author(s): Henry Dillon (Independent Consultant, UK)and Beverley Hope (Victoria University of Wellington, New Zealand)
Copyright: 2008
Pages: 15
Source title: Data Warehousing and Mining: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-59904-951-9.ch170

Keywords: Data Mining and Databases / Data Warehousing / Information Science Reference / Library & Information Science

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Abstract

Knowledge discovery in databases (KDD) is a field of research that studies the development and use of various data analysis tools and techniques. KDD research has produced an array of models, theories, functions and methodologies for producing knowledge from data. However, despite these advances, nearly two thirds of information technology (IT) managers say that data mining products are too difficult to use in a business context. This chapter discusses how advances in data mining translate into the business context. It highlights the art of business implementation rather than the science of KDD.

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Translating Advances in Data Mining in Business Operations: The Art of Data Mining in Retailing

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