The main steps to data quality

Authors:
Joachim Schmid
Affiliations:
FUZZY! Informatik AG, Ludwigsburg, Germany
Venue:
ICDM'04 Proceedings of the 4th international conference on Advances in Data Mining: applications in Image Mining, Medicine and Biotechnology, Management and Environmental Control, and Telecommunications
Year:
2004

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Abstract

To gain knowledge out of your data, your data has to be of high quality. Bad data quality becomes more and more the problem for companies, who start to exploit their data stocks. This article will show the main obstacles on the way to perfect data quality. It is based on our experience to improve data quality in large customer or business partner databases. The examples mentioned in this paper show data defects we have found during our daily work. There are also some notes how to improve data quality and avoid data defects.