Data warehouse enhancement: A semantic cube model approach |
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| Affiliation: | 1. Department of Accounting and Information Technology, National Chung-Cheng University, Chia-Yi, Taiwan;2. Department of Management Information Systems, National Cheng-Chi University, No. 64, Sec. 2, ZhiNan Rd., Wenshan District, Taipei City 11605, Taipei, Taiwan;3. Visiting Fulbright Senior Scholar, Stanford University, and Professor of Information Systems, Graduate School of Accountancy, College of Commerce, National Chengchi University, Wenshan District 116, Taipei, Taiwan;1. University Politehnica of Bucharest, Department of Computer Science, 313 Splaiul Independentei, 060042 Bucharest, Romania;2. Ecole Nationale Supérieure des Mines, FAYOL-EMSE, LSTI, F-42023 Saint-Etienne, France;1. Pervasive Systems (PS), University of Twente, The Netherlands;2. Centre for Transport Studies (CTS), University of Twente, The Netherlands;3. Computer and Communication Systems, Institute of Computer Science, University of Innsbruck, Austria;1. INGAR (CONICET/Universidad Tecnológica Nacional), Avellaneda 3657, 3000 Santa Fe, Argentina;2. INTEC (Universidad Nacional del Litoral, CONICET), Ruta Nacional 168, Km 0, 3000 Santa Fe, Argentina;1. School of Automation, Huazhong University of Science and Technology, Wuhan 430074, China;2. National Key Laboratory of Science and Technology on Multi-Spectral Information Processing, Huazhong University of Science and Technology, Wuhan 430074, China;3. Key Laboratory for Image Information Processing and Intelligence Control of Education Ministry, Huazhong University of Science and Technology, Wuhan 430074, China;4. National Key Laboratory of Science and Technology on Aerospace Intelligence Control, Beijing 100101, China |
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| Abstract: | Many data warehouse systems have been developed recently, yet data warehouse practice is not sufficiently sophisticated for practical usage. Most data warehouse systems have some limitations in terms of flexibility, efficiency, and scalability. In particular, the sizes of these data warehouses are forever growing and becoming overloaded with data, a scenario that leads to difficulties in data maintenance and data analysis. This research focuses on data-information integration between data cubes. This research might contribute to the resolution of two concerns: the problem of redundancy and the problem of data cubes’ independent information. This work presents a semantic cube model, which extends object-oriented technology to data warehouses and which enables users to design the generalization relationship between different cubes. In this regard, this work’s objectives are to improve the performance of query integrity and to reduce data duplication in data warehouse. To deal with the handling of increasing data volume in data warehouses, we discovered important inter-relationships that hold among data cubes, that facilitate information integration, and that prevent the loss of data semantics. |
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