大葉大學圖書館 |

Data quality management with semantic technologies[electronic resource] /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	005.7565
書名/作者:	Data quality management with semantic technologies/ by Christian Furber.
作者:	Furber, Christian.
出版者:	Wiesbaden : : Springer Fachmedien Wiesbaden :, 2016.
面頁冊數:	xxvii, 205 p. : : ill., digital ;; 24 cm.
Contained By:	Springer eBooks
標題:	Database management.
標題:	Databases - Quality control.
標題:	Semantic Web.
標題:	Business and Management.
標題:	Business Information Systems.
標題:	Knowledge Management.
ISBN:	9783658122256
ISBN:	9783658122249
摘要、提要註:	Christian Furber 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. Contents Data Quality and Semantic Technology Basics Data Quality in the Semantic Web Architecture and Evaluation of the Semantic Data Quality Management Framework Target Groups Researchers and students in the fields of economics, information systems and computer science Practitioners in the areas of data management, process management and business intelligence The Author Dr. Christian Furber completed his doctoral study under the supervision of Prof. Dr. Martin Hepp at the E-Business and Web Science Research Group of the Universitat der Bundeswehr Munchen. 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.
電子資源:	http://dx.doi.org/10.1007/978-3-658-12225-6

Data quality management with semantic technologies[electronic resource] /
Furber, Christian.

Data quality management with semantic technologies[electronic resource] /by Christian Furber. - Wiesbaden :Springer Fachmedien Wiesbaden :2016. - xxvii, 205 p. :ill., digital ;24 cm.

Christian Furber 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. Contents Data Quality and Semantic Technology Basics Data Quality in the Semantic Web Architecture and Evaluation of the Semantic Data Quality Management Framework Target Groups Researchers and students in the fields of economics, information systems and computer science Practitioners in the areas of data management, process management and business intelligence The Author Dr. Christian Furber completed his doctoral study under the supervision of Prof. Dr. Martin Hepp at the E-Business and Web Science Research Group of the Universitat der Bundeswehr Munchen. 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.

ISBN: 9783658122256

Standard No.: 10.1007/978-3-658-12225-6doiSubjects--Topical Terms:

174575
Database management.

LC Class. No.: QA76.9.D3 / F73 2016

Dewey Class. No.: 005.7565

Data quality management with semantic technologies[electronic resource] /
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