Data Quality
Subtitle: Concepts, Methodologies and Techniques (Data-Centric Systems and Applications)
Edition: 1 edition
Publisher: Springer
Published: October 9, 2006
Language: eng
Format: Hardcover
Number of pages: 262
ISBN-13: 9783540331728
Subjects: Databases & data structures; Information Technology; Computers - Data Base Management; Computers; Computer Books: Database; Database Management - General; Information Storage & Retrieval; Computers / Database Management / General; Data Accuracy; Data Availability; Data Completeness; Data Consistency; Data Integration; Data Quality; Distributed Data Management; Database management; Databases; Quality control
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.