Assessing the Importance of Data Factors of Data Quality Model in the Business Intelligence Area

Abstract

Business Intelligence (BI) is defined as the intelligent transfer of data from all variety of sources with a view to providing a real time quantification of business performance. Moreover, by utilizing BI senior managers are able to make better-informed decisions, guided by the integration of comprehensive information from all facets of an organization in real time. Further, the quality of corporate decision making is directly dependent upon the quality of data. Quality dimensions have proven to be of importance in evaluating how an organization understands and manages its data. Hence, in this study we employed the data quality model of Wang and Strong as our benchmark, and by questioning experts five additional factors (Usefulness, Efficiency, Availability, Navigation, and Usability) were added to the model to improve the reference model. Furthermore, the importance of these factors (and how they relate to each other, in terms of their dimensions) will be measured by the AHP method and an expert panel. Finally, we will reveal how the findings demonstrate that the intrinsic, contextual, representational and accessibility IQs in terms of their dimensions and reputation, accuracy, believability, and reliability, proved to be the most important factors..