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Article Information:
Title:
A knowledge management approach to data mining process for business intelligence
Author(s):
Hai Wang, Shouhong Wang
Journal:
Industrial Management & Data Systems
Year:
2008
Volume:
Issue:
Page:
622 - 634
ISSN:
0263-5577
DOI:
10.1108/02635570810876750
Publisher:
Emerald Group Publishing Limited
Acknowledgements:
The comments of two anonymous reviewers have contributed significantly to the revision of the paper. The first author is supported in part by Natural Sciences and Engineering Research Council of Canada (NSERC Grant 312423).
Document Access:
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:
Blogs, Business intelligence, Data mining, Knowledge management, Knowledge sharing
Article Type:
Research paper