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.
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© 2004 Springer-Verlag Berlin Heidelberg
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Schmid, J. (2004). The Main Steps to Data Quality. In: Perner, P. (eds) Advances in Data Mining. ICDM 2004. Lecture Notes in Computer Science(), vol 3275. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30185-1_8
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DOI: https://doi.org/10.1007/978-3-540-30185-1_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-24054-9
Online ISBN: 978-3-540-30185-1
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