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The data warehouse virtualization framework for operational business intelligence



In order to explore the most current information and react faster to changing business conditions, organizations consider real-time data warehousing a powerful technique to achieve operational business intelligence (BI). We propose in this paper a novel real-time data warehouse (RTDW) framework based on the virtualization concept. Our approach introduces a conceptual modelling technique, known as ring modelling, for real-time data management and multidimensional analysis. This technique produces a flexible semi-structured data model that accommodates unknown business process data and relationships as they evolve, handles schema changes and aggregate-management efficiently, and scales well with the large size of increasing data volumes. With the help of a telecommunication business example, We evaluated our proposed approach in an extensive experimental study where we compared our approach Ring Model with existing structured multidimensional conceptual models (MCMs), i.e. relational OLAP and multidimensional OLAP, and with semi-structured MCM, i.e. XML Cubes, in terms of scalability, data storage estimations, data updates loading time, and query response times. Our performance results show that encouraging speedups are achieved.