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Data Mining and the Project Management Environment

Data Mining and the Project Management Environment

Emanuel Camilleri
Copyright: © 2010 |Pages: 21
ISBN13: 9781605669069|ISBN10: 1605669067|ISBN13 Softcover: 9781616923075|EISBN13: 9781605669076
DOI: 10.4018/978-1-60566-906-9.ch017
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MLA

Camilleri, Emanuel. "Data Mining and the Project Management Environment." Data Mining in Public and Private Sectors: Organizational and Government Applications, edited by Antti Syvajarvi and Jari Stenvall, IGI Global, 2010, pp. 337-357. https://doi.org/10.4018/978-1-60566-906-9.ch017

APA

Camilleri, E. (2010). Data Mining and the Project Management Environment. In A. Syvajarvi & J. Stenvall (Eds.), Data Mining in Public and Private Sectors: Organizational and Government Applications (pp. 337-357). IGI Global. https://doi.org/10.4018/978-1-60566-906-9.ch017

Chicago

Camilleri, Emanuel. "Data Mining and the Project Management Environment." In Data Mining in Public and Private Sectors: Organizational and Government Applications, edited by Antti Syvajarvi and Jari Stenvall, 337-357. Hershey, PA: IGI Global, 2010. https://doi.org/10.4018/978-1-60566-906-9.ch017

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Abstract

The chapter illustrates how data mining and knowledge management concepts may be applied in a project oriented environment for both the private and public sectors. It identifies the project environment success roadmap that consists of four levels leading to project corporate success. Processes that control the dataflow for generating the projects data warehouse are identified and the projects data warehouse contents are defined. The rest of the chapter shows how data mining may be utilised at each project success level to increase the chances of delivering profitable projects that will have the intended impact on the corporate business strategy. The general conclusion is that there is a need to structure and prioritise information for specific end-user problems and to address a number of organizational issues that may facilitate the application of data mining and knowledge management in a project oriented environment. Finally, the chapter concludes by identifying the issues that need to be addressed by private and public sector organizations so that data mining may be utilised successfully in their decision making process.

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