Quality Assessment of Data Using Statistical and Machine Learning Methods

Data warehouses are used in organization for efficiently managing the information. The data from various heterogeneous data sources are integrated in data warehouse in order to do analysis and make decision. Data warehouse quality is very important as it is the main tool for strategic decision. Data warehouse quality is influenced by Data model quality which is further influenced by conceptual data model. In this paper, we first summarize the set of metrics for measuring the understand ability of conceptual data model for data warehouses. The statistical and machine learning methods are used to predict effect of structural metrics, on understand ability, efficiency and effectiveness of Data warehouse Multidimensional (MD) conceptual model.