Encyclopedia of Database Systems

2018 Edition
| Editors: Ling Liu, M. Tamer Özsu

Quality of Data Warehouses

  • Rafael Romero
  • Jose-Norberto Mazón
  • Juan Trujillo
  • Manuel Serrano
  • Mario Piattini
Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-8265-9_289

Definition

Quality is an abstract and subjective aspect for which there is no universal definition. It is usually said that there is a quality definition for each person. Perhaps the most abstract definition for this topic is that the data warehouse quality means the data is suitable for the intended application by all users. In this way, it is very complex to measure or assess the quality of a data warehouse system. Normally, the data warehouse quality is determined by (i) the quality of the data presentation and (ii) the quality of the data warehouseitself. The latter is determined by the quality of the database management system (DBMS), the data quality, and the quality of the underlying data models used to design it. A good design may (or may not) lead to a good data warehouse, but a bad design will surely render a bad data warehouse of low quality. In order to measure the quality of a data warehouse, a key issue is defining and validating a set of metrics to help to assess the...

This is a preview of subscription content, log in to check access.

Recommended Reading

  1. 1.
    Basili V, Weiss DA. Methodology for collecting valid software engineering data. IEEE Trans Softw Eng. 1984;10(6):728–38.CrossRefGoogle Scholar
  2. 2.
    Briand L, Morasca S, Basili V. Property-based software engineering measurement. IEEE Trans Softw Eng. 1996;22(1):68–86.CrossRefGoogle Scholar
  3. 3.
    Golfarelli M, Rizzi S. Data warehouse testing: a prototype-based methodology. Inf Softw Technol. 2011;53(11):1183–98.CrossRefGoogle Scholar
  4. 4.
    ISO/IEC 25010:2010(E). Systems and software engineering – Systems and Software Product Quality Requirements and Evaluation (SQuaRE) – system and software quality models. Geneva: International Organization for Standardization; 2010.Google Scholar
  5. 5.
    ISO/IEC 9075. Database languages – SQL. Information Technology; 2008Google Scholar
  6. 6.
    Jarke M, Lenzerini M, Vassiliou Y, Vassiliadis P. Fundamentals of data warehouses. Berlin: Springer; 2010.zbMATHGoogle Scholar
  7. 7.
    Jeusfeld MA, Quix C, Jarke M. Design and analysis of quality information for data warehouses. In: Proceedings of the 17th International Conference on Conceptual Modeling; 1998. p. 349–62.CrossRefGoogle Scholar
  8. 8.
    Lechtenbörger J, Vossen G. Multidimensional normal forms for data warehouse design. Inf Syst. 2003;28(5):415–34.zbMATHCrossRefGoogle Scholar
  9. 9.
    Lehner W, Albretch J, Wedekind H. Normal forms for multidimensional databases. In: Proceedings of the 10th International Conference on Scientific and Statistical Database Management; 1998. p. 63–72.Google Scholar
  10. 10.
    Othayoth R, Poess M. The making of TPC-DS. In: Proceedings of the 32nd International Conference on Very Large Data Bases; 2006. p. 1049–58.Google Scholar
  11. 11.
    Poels G, Dedene G. DISTANCE: a framework for software measure construction, Research report DTEW9937, Katholieke Universiteit Leuven; 1999. p. 46.Google Scholar
  12. 12.
    Serrano M, Calero C, Piattini M. Validating metrics for data warehouses. IEE Proc Softw. 2002;149(5):161–6.CrossRefGoogle Scholar
  13. 13.
    Serrano M, Trujillo J, Calero C, Piattini M. Metrics for data warehouse conceptual models understandability. Inf Softw Technol. 2007;49(8):851–70.CrossRefGoogle Scholar
  14. 14.
    Si-Saïd S., Prat N. Multidimensional schemas quality: assessing and balancing analyzability and simplicity. In: Proceedings of the 22nd International Conference on Conceptual Modeling; 2003. p. 140–51.Google Scholar
  15. 15.
    Vassiliadis P. Data warehouse modeling and quality issues. PhD thesis. Athens: National Technical University of Athens; 2000.Google Scholar
  16. 16.
    Wohlin C, Runeson P, Höst M, Ohlson M, Regnell B, Wesslén A. Experimentation in software engineering. Heidelberg: Springer; 2012.zbMATHCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Rafael Romero
    • 1
  • Jose-Norberto Mazón
    • 1
  • Juan Trujillo
    • 3
  • Manuel Serrano
    • 1
  • Mario Piattini
    • 2
  1. 1.University of AlicanteAlicanteSpain
  2. 2.University of Castilla-La ManchaCiudad RealSpain
  3. 3.Lucentia Research Group, Department of Information Languages and SystemsFacultad de Informática, University of AlicanteAlicanteSpain

Section editors and affiliations

  • Torben Bach Pedersen
    • 1
  • Stefano Rizzi
    • 2
  1. 1.Department of Computer ScienceAalborg UniversityAalborgDenmark
  2. 2.DISIUniversity of BolognaBolognaItaly