Overview
- Publication in the field of economic sciences
- Includes supplementary material: sn.pub/extras
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Table of contents (11 chapters)
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Front Matter
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Back Matter
Keywords
About this book
Christian Fürber investigates the useful application of semantic technologies for the area of data quality management. Based on a literature analysis of typical data quality problems and typical activities of data quality management processes, he develops the Semantic Data Quality Management framework as the major contribution of this thesis. The SDQM framework consists of three components that are evaluated in two different use cases. Moreover, this thesis compares the framework to conventional data quality software. Besides the framework, this thesis delivers important theoretical findings, namely a comprehensive typology of data quality problems, ten generic data requirement types, a requirement-centric data quality management process, and an analysis of related work.
Authors and Affiliations
About the author
Dr. Christian Fürber completed his doctoral study under the supervision of Prof. Dr. Martin Hepp at the E-Business and Web Science Research Group of the Universität der Bundeswehr München. He is founder and CEO of the Information Quality Institute GmbH, a company that consults organizations of any size to improve the quality of their data.
Bibliographic Information
Book Title: Data Quality Management with Semantic Technologies
Authors: Christian Fürber
DOI: https://doi.org/10.1007/978-3-658-12225-6
Publisher: Springer Gabler Wiesbaden
eBook Packages: Business and Management, Business and Management (R0)
Copyright Information: Springer Fachmedien Wiesbaden 2016
Softcover ISBN: 978-3-658-12224-9Published: 05 January 2016
eBook ISBN: 978-3-658-12225-6Published: 11 December 2015
Edition Number: 1
Number of Pages: XXVII, 205
Number of Illustrations: 63 b/w illustrations