Comprehensive complexity metric for data warehouse multidimensional model understandability

• Published in: IET software Vol. 14; no. 3; pp. 275 - 282
• Main Authors: Gosain, Anjana, Singh, Jaspreeti
• Format: Journal Article
• Language: English
• Published: The Institution of Engineering and Technology 01.06.2020
• Subjects: complexity measure; comprehensive complexity metric; correlation regression; data warehouse development; data warehouse multidimensional model understandability; data warehouse quality; data warehouses; hierarchy levels; hierarchy types; multidimensional model complexity; multinomial regression; regression analysis; software metrics; software quality; Special Issue: Knowledge Discovery for Software Development (KDSD); statistical techniques; structural complexity; statistical techniques; data warehouse development; hierarchy levels; regression analysis; comprehensive complexity metric; complexity measure; software quality; multidimensional model complexity; multinomial regression; correlation regression; data warehouse quality; hierarchy types; structural complexity; data warehouse multidimensional model understandability; data warehouses; software metrics

Data warehouse quality can be determined during the initial phases of data warehouse development by quantifying the structural complexity of multidimensional models using metrics. The structural complexity of a multidimensional model is guided by its elements, types, and relationships among those el...