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Titlebook: Data Quality; Concepts, Methodolog Carlo Batini,Monica Scannapieca Book 2006 Springer-Verlag Berlin Heidelberg 2006 Data Accuracy.Data Avai

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書目名稱Data Quality
副標題Concepts, Methodolog
編輯Carlo Batini,Monica Scannapieca
視頻videohttp://file.papertrans.cn/264/263028/263028.mp4
概述Details and analyzes different quality dimension definitions and parameters.Combines approaches from data modeling, data mining, knowledge representation, probability theory, statistical data analysis
叢書名稱Data-Centric Systems and Applications
圖書封面Titlebook: Data Quality; Concepts, Methodolog Carlo Batini,Monica Scannapieca Book 2006 Springer-Verlag Berlin Heidelberg 2006 Data Accuracy.Data Avai
描述.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
出版日期Book 2006
關鍵詞Data Accuracy; Data Availability; Data Completeness; Data Consistency; Data Integration; Data Quality; Dis
版次1
doihttps://doi.org/10.1007/3-540-33173-5
isbn_softcover978-3-642-06970-3
isbn_ebook978-3-540-33173-5Series ISSN 2197-9723 Series E-ISSN 2197-974X
issn_series 2197-9723
copyrightSpringer-Verlag Berlin Heidelberg 2006
The information of publication is updating

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Book 2006related 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
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Introduction to Data Quality,ssed. While data quality is a relatively new research area, other areas, such as statistical data analysis, have addressed in the past some aspects of the problems related to data quality; with statistical data analysis, also knowledge representation, data mining, management information systems, and
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