Framework for formal implementation of the business understanding phase of data mining projects

Abstract

Various data mining methodologies have been proposed in the literature to provide guidance towards the process of implementing data mining projects. The methodologies describe a data mining project as comprised of a sequence of phases and highlight the particular tasks and their corresponding activities to be performed during each of the phases. It seems that the large number of tasks and activities, often presented in a checklist manner, are cumbersome to implement and may explain why all the recommended tasks are not always formally implemented. Additionally, there is often little guidance provided towards how to implement a particular task. These issues seem to be especially dominant in case of the business understanding phase which is the foundational phase of any data mining project. In this paper, we present an organizationally grounded framework to formally implement the business understanding phase of data mining projects. The framework serves to highlight the dependencies between the various tasks of this phase and proposes how and when each task can be implemented. An illustrative example of a credit scoring application from the financial sector is used to exemplify the tasks discussed in the proposed framework.