Post Data Mining Analysis for Decision Support through Econometrics

Article type: Research Article

Authors: Forgionne, Guisseppi A. | Rubenstein-Montano, Bonnie

Affiliations: Information Systems Department, University of Maryland Baltimore County, Catonsville, Maryland 21228, USA

Note: [] Corresponding author: G.A. Forgionne, Information Systems Department, University of Maryland Baltimore County, Catonsville, Maryland 21228, USA, Tel.: +1 410 455 3943, Fax: +1 410 455 1073, E-mail: Forgionn@UMBC7.UMBC.EDU

Abstract: Data warehousing and data mining are important tools for creating information that is relevant for decision making.  Still, much additional post data mining analysis is needed to provide complete decision making support.  Econometric models offer additional tools that can transform data mining information into knowledge for effective decision making.  This manuscript discusses the role of data mining in decision support, outlines the shortcomings of the approach, and examines how these shortcomings can be reduced through econometrics.  The concepts are illustrated with an application at the U.S. Department of Defense.  Implications for decision support are then discussed

Journal: Information, Knowledge, Systems Management, vol. 1, no. 2, pp. 145-157, 1999