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Dimension Hierarchies Design from UML Generalizations and Aggregations

  • Jacky Akoka
  • Isabelle Comyn-Wattiau
  • Nicolas Prat
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2224)

Abstract

Data for decision-making applications are based on dimensions, such as time, customer, and product. These dimensions are naturally related by hierarchies. Hierarchies are crucial to multidimensional modeling. Defining hierarchies using star or snowflake schemas can be misleading, since they are not explicitly well-modeled. However, deriving them from conceptual UML or ER schemas is a non-trivial task since they have no direct equivalent in conceptual models. This paper focuses on the definition of multidimensional hierarchies. We present and illustrate rules for defining multidimensional hierarchies from UML schemas, especially based on aggregation and generalization hierarchies. The definition of hierarchies is part of a data warehouse design method based on the three usual modeling levels : conceptual, logical, and physical. The conceptual schema is based on the UML notation. The logical schema is represented using a unified pivot multidimensional model. The physical schema depends on the target ROLAP or MOLAP tool.

Keywords

Unify Modeling Language Data Warehouse Mapping Rule Minimum Cardinality Multidimensional Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Jacky Akoka
    • 1
  • Isabelle Comyn-Wattiau
    • 2
  • Nicolas Prat
    • 3
  1. 1.CEDRIC-CNAM & INTPARIS Cedex 03France
  2. 2.Université de Cergy & ESSECPONTOISE CedexFrance
  3. 3.ESSECCERGY CedexFrance

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