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Managing Complex Multidimensional Data

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Business Intelligence (eBISS 2012)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 138))

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Abstract

Multidimensional database concepts such as cubes, dimensions with hierarchies, and measures are a cornerstone of business intelligence. However, the standard data models and system implementations (OLAP) for multidimensional databases are sometimes not able to capture the complexities of advanced real-world application domains. This lecture will focus on how to manage such complex multidimensional data, including complex dimension hierarchies, complex measures, and integration of multidimensional data with complex external data. We will look at how complex multidimensional data emerge in complex application domains such as medical data, location-based services, music data, web data, and text data, and present solutions for these domains that support multidimensional business intelligence.

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Author information

Authors and Affiliations

  1. Aalborg University, 9220, Aalborg Ø, Denmark

    Torben Bach Pedersen

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  1. Torben Bach Pedersen
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Editors and Affiliations

  1. MAS Laboratory, Ecole Centrale Paris, Châtenay-Malabry, France

    Marie-Aude Aufaure

  2. Department of Computer and Decision Engineering (CoDE), Université Libre de Bruxelles, Brussels, Belgium

    Esteban Zimányi

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Pedersen, T.B. (2013). Managing Complex Multidimensional Data. In: Aufaure, MA., Zimányi, E. (eds) Business Intelligence. eBISS 2012. Lecture Notes in Business Information Processing, vol 138. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36318-4_1

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  • DOI: https://doi.org/10.1007/978-3-642-36318-4_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-36317-7

  • Online ISBN: 978-3-642-36318-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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