Quality in Data Warehousing

  • Mokrane Bouzeghoub
  • Zoubida Kedad
Chapter
Part of the Advances in Database Systems book series (ADBS, volume 25)

Abstract

Data warehousing is a new technology which provides a software infrastructure for decision support systems and OLAP applications. Data warehouse systems collect data from heterogeneous and distributed sources, transform and reconcile this data in order to aggregate it and customize it with respect to business and organizational criteria required by decision makers. High level aggregated data is organized by subjects and stored as a multidimensional structure into a data mart. Data quality is very important in database applications in general and very crucial in data warehousing in particular. Indeed, data warehouse systems provide aggregated data to decision makers whose actions and decisions should be very strategic to the enterprise. Providing dirty data, imprecise data or non coherent data may lead to the rejection of the decision support system or may result into non productive decisions. This chapter provides a general framework for data warehouse design based on quality.

Keywords

Quality Factor Data Warehouse Enterprise Model Quality Goal User View 
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 Science+Business Media New York 2002

Authors and Affiliations

  • Mokrane Bouzeghoub
    • 1
  • Zoubida Kedad
    • 1
  1. 1.Laboratoire PRiSMUniversity of VersaillesFrance

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