Data Warehouses: Next Challenges

  • Alejandro Vaisman
  • Esteban Zimányi
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 96)


Data Warehouses are a fundamental component of today’s Business Intelligence infrastructure. They allow to consolidate heterogeneous data from distributed data stores and transform it into strategic indicators for decision making. In this tutorial we give an overview of current state of the art and point out to next challenges in the area. In particular, this includes to cope with more complex data, both in structure and semantics, and keeping up with the demands of new application domains such as Web, financial, manufacturing, genomic, biological, life science, multimedia, spatial, and spatiotemporal applications. We review consolidated resaerch in spatio-temporal databases, and open research fields, like real-time Business Intelligence and Semantic Web Data Warehousing and OLAP.


data warehouses OLAP spatiotemporal data warehouses realtime data warehouses semantic data warehouses 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Alejandro Vaisman
    • 1
  • Esteban Zimányi
    • 1
  1. 1.Department of Computer and Decision Engineering (CoDE)Université Libre de BruxellesBelgium

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