Empirical validation of metrics for object oriented multidimensional model for data warehouse

Abstract

Metrics have been popularly used to guide designers to develop quality data models. Researchers have proposed metrics for multidimensional models for data warehouses. These metrics need to be empirically validated to prove their practical utility. This paper presents the empirical validation of the metrics for multidimensional models for data warehouses at conceptual level. Quality attributes namely, understandability and efficiency are evaluated through various combinations of metrics. Multiple linear regression analysis has been used in this paper for predicting the multidimensional models quality. The results show that these metrics may be considered as solid indicators for quality of multidimensional data models. Finally, accuracy of our models in predicting the multidimensional models’ quality is evaluated.