Evaluation of data warehouse quality from conceptual model perspective

Abstract

Organizations are adopting Data Warehouse (DW) for making strategic decisions. DW consist of huge and complex set of data, thus its maintenance and quality are equally important. Using improper, misunderstood, disregarded data quality will highly impact the decision making process as well as its performance. The DW quality is depending on data model quality, DBMS quality and Data quality itself. In this paper, we have surveyed on two aspects of DW quality; one is how researchers have improved the quality of Data; and another is how data model quality is improved. The paper discusses that metrics are real quality indicators of DWs; they help the designers in obtaining good quality model that allows us to guarantee the quality of the DW. In this paper, our focus has been on surveying research papers with respect to quality of the multidimensional conceptual model of DW. Having surveyed various papers, we compared all the proposals concerning theoretical validation and empirical validation of conceptual model metrics for assessment of DW model quality.