A conceptual framework to organize large volume of data for business intelligence

A conceptual framework is proposed in this paper for organizing the enormous volume of data having business information using data mining techniques to retrieve information and knowledge useful in supporting complex decision-making processes. A heuristic approach for organizing business data is adopted, which allows us to create, confirm, or contradict a hypothesis. This is accomplished through the use of intelligent agents that act as conceptual “Data Crowed-Puller” (DCP). These DCPs attract fundamental pieces of business information. The central part of design is the support for queries, both ad-hoc and long standing, which also acts as DCPs attracting the relevant information that a human analyst needs to estimate the validity of the hypothesis.