Architecture and Quality in Data Warehouses

  • Matthias JarkeEmail author
  • Manfred A. Jeusfeld
  • Christoph Quix
  • Panos Vassiliadis


Most database researchers have studied data warehouses (DW) in their role as buffers of materialized views, mediating between updateintensive OLTP systems and query-intensive decision support. This neglects the organizational role of data warehousing as a means of centralized information flow control. As a consequence, a large number of quality aspects relevant for data warehousing cannot be expressed with the current DW meta models. This paper makes two contributions towards solving these problems. Firstly, we enrich the meta data about DW architectures by explicit enterprise models. Secondly, many very different mathematical techniques for measuring or optimizing certain aspects of DW quality are being developed. We adapt the Goal-Question-Metric approach from software quality management to a meta data management environment in order to link these special techniques to a generic conceptual framework of DW quality. Initial feedback from ongoing experiments with a partial implementation of the resulting meta data structure in three industrial case studies provides a partial validation of the approach.


Data Warehouse Quality Function Deployment Enterprise Model Quality Goal Conceptual Perspective 
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 2013

Authors and Affiliations

  • Matthias Jarke
    • 1
    Email author
  • Manfred A. Jeusfeld
    • 2
  • Christoph Quix
    • 1
  • Panos Vassiliadis
    • 3
  1. 1.RWTH AachenAachenGermany
  2. 2.Tilburg UniversityTilburgThe Netherlands
  3. 3.National Technical University of AthensAthensGreece

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