A Framework for Organizational Data Analysis and Organizational Data Mining
A Framework for Organizational Data Analysis and Organizational Data Mining

A Framework for Organizational Data Analysis and Organizational Data Mining

From Business Objectives to Steps of Action

Beitrag, Englisch

Autor: Prof. Dr. Bernd Knobloch

Erscheinungsdatum: 2003

Quelle: In: Nemati, H.; Barko, C. (Hrsg.): Organizational Data Mining: Leveraging Enterprise Data Resources for Optimal Performance

Seitenangabe: 334 - 356


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Abstract: This chapter introduces a framework for organizational data analysis suited for data-driven and hypotheses-driven problems. It shows why knowledge discovery and hypothesis verification are complementary approaches and how they can be chained together. It presents a methodology for organizational data analysis including a comprehensive processing scheme. Employing a plug-in metaphor, data analysis process engineering is introduced as a way to set up data analysis processes based on taxonomies of tasks that have to be performed during data analysis and on the idea of re-using experience from past data analysis projects. The framework aims at increasing the benefits of data mining and other data analysis approaches by allowing a wider range of business problems to be tackled and by providing the users with structured guidance for planning and running analyses.

Prof. Dr. Bernd Knobloch

DE, Kulmbach

Freiberufler

Systemberatung für Wirtschaftsinformatik

Publikationen: 8

Aufrufe seit 10/2005: 2232
Aufrufe letzte 30 Tage: 2