A concurrent group decision-making framework for selection of business intelligence–based data warehouse architecture

Abstract

The selection of an appropriate data warehouse architecture from a business intelligence–based perspective is an important decision to achieve organizational strategies. The aim of this article is to develop a concurrent group decision-making framework for the selection of a data warehouse business intelligence–based architecture. In this framework, in order to translate higher level needs into lower level requirements, we develop a four-level concurrent decision-making model to turn (1) critical success factors of business intelligence implementation into key data mining factors at the first level, (2) the key data mining factors into key ontology factors at the second level, and (3) the key ontology factors into key data resource management factors at the third level. Then, these factors are utilized to select the business intelligence data warehouse architecture at the fourth level of the four-level concurrent decision-making model. A case study demonstrates the applicability of the concurrent group decision-making framework.