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A Distributed Multidimensional Data Model of Data Warehouse

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Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing (RSFDGrC 2003)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2639))

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Abstract

The base fact tables of a data warehouse are generally of huge size. In order to shorten query response time and to improve maintenance performance, a base fact table is generally partitioned into multiple instances of same schema. To facilitate multidimensional data analysis, common methods are to create different multidimensional data models (MDDM) for different instances which may make it difficult to realize transparent multi-instance queries and maintenance. To resolve the problems, this paper proposes a logically integrated and physically distributed multidimensional data model.

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References

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© 2003 Springer-Verlag Berlin Heidelberg

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Lin, Y., Huang, H., Li, H. (2003). A Distributed Multidimensional Data Model of Data Warehouse. In: Wang, G., Liu, Q., Yao, Y., Skowron, A. (eds) Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. RSFDGrC 2003. Lecture Notes in Computer Science(), vol 2639. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-39205-X_112

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  • DOI: https://doi.org/10.1007/3-540-39205-X_112

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-14040-5

  • Online ISBN: 978-3-540-39205-7

  • eBook Packages: Springer Book Archive

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