Theory and support for process frameworks of knowledge discovery and data mining from ERP systems

Existing theory has framed the process of information extraction and agglomeration, also referred to as the knowledge discovery (KD) process, as a series of strategic search decisions, subject to constraints, with the objective of attaining a sufficient level of domain-specific knowledge for use in strategic planning. Supported by the experiences of firms representative of Client, Developer, and Third-party segments of the data mining (DM) community, this work provides an extension to this basic framework. The implications provided suggest a wealth of untapped opportunities in the area of KD research.