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.
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;
Conference_Titel :
Scientific and Statistical Database Management, 2006. 18th International Conference on
Conference_Location :
Vienna
Print_ISBN :
0-7695-2590-3
DOI :
10.1109/SSDBM.2006.20