Advertisement

Evolution-Oriented User-Centric Data Warehouse

  • Darja SolodovnikovaEmail author
  • Laila NiedriteEmail author
Conference paper

Abstract

Data warehouses tend to evolve, because of changes in data sources and business requirements of users. All these kinds of changes must be properly handled, therefore, data warehouse development is never-ending process. In this paper we propose the evolution-oriented user-centric data warehouse design, which on the one hand allows to manage data warehouse evolution automatically or semi-automatically, and on the other hand it provides users with the understandable, easy and transparent data analysis possibilities. The proposed approach supports versions of data warehouse schemata and data semantics.

Notes

Acknowledgments

This work has been supported by ESF projects No. 2009/0216/1DP/1.1.1.2.0/09/APIA/VIAA/044 and 2009/0138/1DP/1.1.2.1.2/09/IPIA/VIAA/004.

References

  1. 1.
    Golfarelli M, Lechtenbörger J, Rizzi S, Vossen G (2006) Schema versioning in data warehouses: enabling cross-version querying via schema augmentation. Data Knowl Eng 59(2):435–459CrossRefGoogle Scholar
  2. 2.
    Hurtado CA, Mendelzon AO, Vaisman AA (1999) Maintaining data cubes under dimension updates. In: 15th international conference on data engineering. IEEE Computer Society, Sydney, pp 346–357Google Scholar
  3. 3.
    Blaschka M (2000) FIESTA: a framework for schema evolution in multidimensional databases. PhD thesis, Technische Universitat Munchen, GermanyGoogle Scholar
  4. 4.
    Banerjee S, Davis KC (2009) Modeling data warehouse schema evolution over extended hierarchy semantics. J Data Semant XIII, LNCS 5530. Springer, Heidelberg, pp 72–96Google Scholar
  5. 5.
    Marotta A (2000) Data warehouse design and maintenance through schema transformations. Master thesis, Universidad de la República UruguayGoogle Scholar
  6. 6.
    Velegrakis Y, Miller RJ, Popa L (2003) Mapping adaptation under evolving schemas. In: 29th international conference on VLDB. Morgan Kaufmann, Berlin, pp 584–595Google Scholar
  7. 7.
    Bellahsene Z (2002) Schema evolution in data warehouses. Knowl Inf Syst 4:283–304CrossRefGoogle Scholar
  8. 8.
    Rundensteiner EA, Koeller A, Zhang X (2000) Maintaining data warehouses over changing information sources. Commun ACM 43(6):57–62CrossRefGoogle Scholar
  9. 9.
    Wrembel R, Bebel B (2005) Metadata management in a multiversion data warehouse. In: OTM conferences (2), LNCS 3761. Springer, Heidelberg, pp 1347–1364Google Scholar
  10. 10.
    Body M, Miquel M, Bedard Y, Tchounikine A (2002) A multidimensional and multiversion structure for OLAP applications. In: ACM 5th international workshop on data warehousing and OLAP. ACM, McLean, pp 1–6Google Scholar
  11. 11.
    Morzy T, Wrembel R (2004) On querying versions of multiversion data warehouse. In: ACM 7th international workshop on data warehousing and OLAP. ACM, Washington, pp 92–101Google Scholar
  12. 12.
    Solodovnikova D (2007) Data warehouse evolution framework. In: Spring young researcher’s colloquium on database and information systems, Moscow, RussiaGoogle Scholar
  13. 13.
    Object Management Group (2003) Common warehouse metamodel specification, v1.1 http://www.omg.org/cgi-bin/doc?formal/03-03-02Google Scholar
  14. 14.
    Solodovnikova D (2008) Building queries on multiple versions of data warehouse. In: 8th International Baltic conference on DB&IS, Tallinn, Estonia, pp 75–86Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.University of LatviaRigaLatvia

Personalised recommendations