Enterprise Information System and Data Mining

Kenneth D. Lawrence; Dinesh R. Pai; Ronald Klimberg; Sheila M. Lawrence

doi:10.4018/978-1-4666-0279-3.ch016

Enterprise Information System and Data Mining

Kenneth D. Lawrence, Dinesh R. Pai, Ronald Klimberg, Sheila M. Lawrence

School of Business Administration (Harrisburg)

Research output: Chapter in Book/Report/Conference proceeding › Chapter

1 Scopus citations

Abstract

The advent of information technology and the consequent proliferation of information systems have lead to generation of vast amounts of data, both within the organization and across its supply chain. Enterprise information systems (EIS) have added to organizational complexity, and at the same time, created opportunities for enhancing its competitive advantage by utilizing this data for business intelligence purposes. Various data mining tools have been used to gain a competitive edge through these large data bases. In this paper, the authors discuss EIS-aided business intelligence and data mining as applicable to organizational functions, such as supply chain management (SCM), marketing, and customer relationship management (CRM) in the context of EIS.

Original language	English (US)
Title of host publication	Organizational Applications of Business Intelligence Management
Subtitle of host publication	Emerging Trends
Publisher	IGI Global
Pages	228-235
Number of pages	8
ISBN (Electronic)	9781466602809
ISBN (Print)	9781466602793
DOIs	https://doi.org/10.4018/978-1-4666-0279-3.ch016
State	Published - Jan 1 2012

All Science Journal Classification (ASJC) codes

General Economics, Econometrics and Finance
General Business, Management and Accounting
General Engineering

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Cite this

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AB - The advent of information technology and the consequent proliferation of information systems have lead to generation of vast amounts of data, both within the organization and across its supply chain. Enterprise information systems (EIS) have added to organizational complexity, and at the same time, created opportunities for enhancing its competitive advantage by utilizing this data for business intelligence purposes. Various data mining tools have been used to gain a competitive edge through these large data bases. In this paper, the authors discuss EIS-aided business intelligence and data mining as applicable to organizational functions, such as supply chain management (SCM), marketing, and customer relationship management (CRM) in the context of EIS.

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ER -

Enterprise Information System and Data Mining

Abstract

All Science Journal Classification (ASJC) codes

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