Spatial Data Warehouses

  • Alejandro Vaisman
  • Esteban Zimányi
Part of the Data-Centric Systems and Applications book series (DCSA)


It is estimated that about 80% of the data stored in databases has a spatial or location component. Therefore, the location dimension has been widely used in data warehouse and OLAP systems. However, this dimension is usually represented in an alphanumeric, nonspatial manner (i.e., using solely the place name) since these systems are not able to manipulate spatial data. Nevertheless, it is well known that including spatial data in the analysis process can help to reveal patterns that are difficult to discover otherwise. Taking into account the growing demand to incorporate spatial data into the decision-making process, we present in this chapter how data warehouses can be extended with spatial data.


Spatial Data Data Warehouse Spatial Level Topological Constraint Spatial Measure 
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 2014

Authors and Affiliations

  • Alejandro Vaisman
    • 1
  • Esteban Zimányi
    • 2
  1. 1.Instituto Tecnológico de Buenos AiresBuenos AiresArgentina
  2. 2.Université Libre de BruxellesBrusselsBelgium

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