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A knowledge management approach to data mining process for business intelligence

Hai Wang (Sobey School of Business, Saint Mary's University, Halifax, Canada)
Shouhong Wang (Charlton College of Business, University of Massachusetts Dartmouth, Dartmouth, Massachusetts, USA)

Industrial Management & Data Systems

ISSN: 0263-5577

Article publication date: 23 May 2008

Abstract

Purpose

Data mining (DM) has been considered to be a tool of business intelligence (BI) for knowledge discovery. Recent discussions in this field state that DM does not contribute to business in a large‐scale. The purpose of this paper is to discuss the importance of business insiders in the process of knowledge development to make DM more relevant to business.

Design/methodology/approach

This paper proposes a blog‐based model of knowledge sharing system to support the DM process for effective BI.

Findings

Through an illustrative case study, the paper has demonstrated the usefulness of the model of knowledge sharing system for DM in the dynamic transformation of explicit and tacit knowledge for BI. DM can be an effective BI tool only when business insiders are involved and organizational knowledge sharing is implemented.

Practical implications

The structure of blog‐based knowledge sharing systems for DM process can be practically applied to enterprises for BI.

Originality/value

The paper suggests that any significant DM process in the BI context must involve data miner centered DM cycle and business insider centered knowledge development cycle.

Keywords

Citation

Wang, H. and Wang, S. (2008), "A knowledge management approach to data mining process for business intelligence", Industrial Management & Data Systems, Vol. 108 No. 5, pp. 622-634. https://doi.org/10.1108/02635570810876750

Publisher

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Emerald Group Publishing Limited

Copyright © 2008, Emerald Group Publishing Limited