On Data Mining and Knowledge

Understanding data mining (DM) as part of Information Systems (IS) this contribution investigates the question how this subordination is reasoned in a technological and business logical perspective. For this purpose general characteristics of Enterprise Resources Planning Applications (ERP) and Management Information Systems (MIS; including here Decision Support and Expert Systems) are presented. Based on this evaluation it is examined how knowledge and DM are becoming interdependent for Knowledge Management (KM) in organizations. Knowledge is defined along the Penrose’an dichotomy of information and knowledge in the context of resources and services. Validity of knowledge is analyzed from a methodological (quantitative versus qualitative methods) perspective, probing what key characteristics of both method strands are, and how those fit into the discipline of Organizational Studies. Unveiling a relationship between security and information in Penrose, an alternative account of security originating in Foucault is presented. In this security and knowledge become means for standardization of live in order to allow for continuation of an abstracted, socially generated object. Combining arguments about validity of knowledge claims with that of security, DM based knowledge and security are identified as means abstracting from a human core and attempting constraining variability. Against this background researchers and users of DM based knowledge are asked for awareness of the constructed character of IS, and how much of this constructed character is contained in DM based knowledge.