Knowledge Creation Opportunities in the Data Mining Process

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Abstract
Nonaka’s modes of knowledge were used to ground an exploratory study of knowledge creation opportunities in the data mining process. A two-phased research study, including 49 interviews with data analysts and decision makers, was completed. Results support the idea that multiple knowledge creation opportunities exist throughout the data mining process. Prior research has defined a data warehouse as a support system for transforming explicit knowledge into new explicit knowledge by merging, categorizing, reclassifying, and synthesizing data [1]. By expanding the research scope from technology to the process, evidence was found that data analysts convert tacit knowledge to new tacit knowledge through social interaction, tacit knowledge to explicit knowledge through evaluation of data mining results, and explicit knowledge to new tacit knowledge through learning from deployment of a decision. This paper explains how one organization implemented a knowledge-oriented data mining process; results of the implementation are presented.