Data Quality

Concepts, Methodologies and Techniques de

,

Éditeur :

Springer


Collection :

Data-Centric Systems and Applications

Paru le : 2006-09-27

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Description
Poor data quality can seriously hinder or damage the efficiency and effectiveness of organizations and businesses. The growing awareness of such repercussions has led to major public initiatives like the "Data Quality Act" in the USA and the "European 2003/98" directive of the European Parliament. Batini and Scannapieco present a comprehensive and systematic introduction to the wide set of issues related to data quality. They start with a detailed description of different data quality dimensions, like accuracy, completeness, and consistency, and their importance in different types of data, like federated data, web data, or time-dependent data, and in different data categories classified according to frequency of change, like stable, long-term, and frequently changing data. The book's extensive description of techniques and methodologies from core data quality research as well as from related fields like data mining, probability theory, statistical data analysis, and machine learning gives an excellent overview of the current state of the art. The presentation is completed by a short description and critical comparison of tools and practical methodologies, which will help readers to resolve their own quality problems. This book is an ideal combination of the soundness of theoretical foundations and the applicability of practical approaches. It is ideally suited for everyone – researchers, students, or professionals – interested in a comprehensive overview of data quality issues. In addition, it will serve as the basis for an introductory course or for self-study on this topic.
Pages
262 pages
Collection
Data-Centric Systems and Applications
Parution
2006-09-27
Marque
Springer
EAN papier
9783540331728
EAN PDF
9783540331735

Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
26
Taille du fichier
3584 Ko
Prix
94,94 €