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Design and Analysis of Quality Information for Data Warehouses

  • Manfred A. Jeusfeld
  • Christoph Quix
  • Matthias Jarke
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1507)

Abstract

Data warehouses are complex systems that have to deliver highly-aggregated, high quality data from heterogeneous sources to decision makers. Due to the dynamic change in the requirements and the environment, data warehouse system rely on meta databases to control their operation and to aid their evolution. In this paper, we present an approach to assess the quality of the data warehouse via a semantically rich model of quality management in a data warehouse. The model allows stakeholders to design abstract quality goals that are translated to executable analysis queries on quality measurements in the data warehouse’s meta database. The approach is being implemented using the ConceptBase meta database system.

Keywords

Quality Measurement Data Warehouse Data Cube Source Relation Quality Goal 
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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References

  1. [CGMH+94]
    Chawathe, S., Garcia-Molina, H., Hammer, J., Ireland, K., Papakonstantinou, Y., Ullman, J., Widom, J.: The TSIMMIS project: integration of heterogeneous information sources. In: Proc. of IPSI Conference, Tokyo, Japan (1994)Google Scholar
  2. [GJJ*98]
    Gebhardt, M., Jarke, M., Jeusfeld, M.A., Quix, C., Sklorz, S.: Tools for data warehouse quality. In: Proc. 10th Intl. Conf. on Scientific and Statistical Database Management (SSDBM 1998), Capri, Italy, July 1-3 (1998)Google Scholar
  3. [HGMW+95]
    Hammer, J., Garcia-Molina, H., Widom, J., Labio, W., Zhuge, Y.: The Stanford Data Warehousing Project. Data Eng., Special Issue Materialized Views on Data Warehousing 18(2), 41–48 (1995)Google Scholar
  4. [HZ96]
    Hull, R., Zhou, G.: A Framework for supporting data integration using the materialized and virtual approaches. In: Proc. ACM SIGMOD Intl. Conf. Management of Data, Montreal, pp. 481–492 (1996)Google Scholar
  5. [Jans88]
    Janson, M.: Data quality: the Achilles heel of end-user computing. Omega J. Management Science 16(5) (1988)Google Scholar
  6. [JGJ+95]
    Jarke, M., Gallersdörfer, R., Jeusfeld, M.A., Staudt, M., Eherer, S.: ConceptBase - a deductive object base for meta data management. Journal of Intelligent Information Systems 4(2), 167–192 (1995)CrossRefGoogle Scholar
  7. [JJQ*98]
    Jarke, M., Jeusfeld, M.A., Quix, C., Vassiliadis, P.: Architecture and quality in data warehouses. In: Pernici, B., Thanos, C. (eds.) CAiSE 1998. LNCS, vol. 1413, pp. 93–113. Springer, Heidelberg (1998)CrossRefGoogle Scholar
  8. [JV97]
    Jarke, M., Vassiliou, Y.: Foundations of data warehouse quality. a review of the DWQ project. In: Proc. 2nd Intl. Conf. Information Quality (IQ 1997), Cambridge, Mass (1997)Google Scholar
  9. [KLSS95]
    Kirk, T., Levy, A.Y., Sagiv, Y., Srivastava, D.: The Information Manifold. In: Proc. AAAI 1995 Spring Symp. on Information Gathering from Heterogeneous, Distributed Environments, pp. 85–91 (1995)Google Scholar
  10. [MBJK90]
    Mylopoulos, J., Borgida, A., Jarke, M., Koubarakis, M.: Telos – a language for representing knowledge about information systems. ACM Trans. Information Systems 8(4), 325–362 (1990)CrossRefGoogle Scholar
  11. [OB92]
    Oivo, M., Basili, V.: Representing software engineering models: the TAME goal-oriented approach. IEEE Trans. Software Eng. 18(10) (1992)Google Scholar
  12. [Wie92]
    Wiederhold, G.: Mediators in the architecture of future information systems. IEEE Computer, 38–49 (March 1992)Google Scholar
  13. [WRK95]
    Wang, R.Y., Reddy, M.P., Kon, H.B.: Towards quality data: an attribute-based approach. Decision Support Systems 13 (1995)Google Scholar
  14. [WSF95]
    Wang, R.Y., Storey, V.C., Firth, C.P.: A framework for analysis of data quality research. IEEE Trans. Knowledge and Data Eng. 7(4) (1995)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • Manfred A. Jeusfeld
    • 1
  • Christoph Quix
    • 2
  • Matthias Jarke
    • 2
  1. 1.INFOLABTilburg UniversityTilburgThe Netherlands
  2. 2.RWTH AachenInformatik VAachenGermany

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