• DocumentCode
    2121752
  • Title

    Edits - Data Cleansing at the Data Entry to assert semantic Consistency of metric Data

  • Author

    Lenz, H.-J. ; Koppen, Veit ; Muller, R.M. ; Berlin, F.

  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    235
  • Lastpage
    240
  • Abstract
    It is a matter of fact that the input of numeric data into databases needs careful screening to avoid semantic incoherency with respect to the knowledge at hand. In nearly all real applications such knowledge exists as models, i.e. as balance equations, behavioral equations or simply as definitions. The representation of those objects is possible by validation rules ("edits"), which are roughly speaking specially tailored tests. The methodology is presented, recent work in progress is shown, and a business application is presented
  • Keywords
    data integrity; data mining; fuzzy set theory; probability; OLAP; OLTP; balance equations; behavioral equations; business application; data cleansing; semantic consistency; Business; Databases; Decision making; Equations; Error analysis; Fuzzy logic; Information systems; Marketing and sales; Measurement errors; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Scientific and Statistical Database Management, 2006. 18th International Conference on
  • Conference_Location
    Vienna
  • ISSN
    1551-6393
  • Print_ISBN
    0-7695-2590-3
  • Type

    conf

  • DOI
    10.1109/SSDBM.2006.20
  • Filename
    1644319