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Books > Computing & IT > Applications of computing > Databases
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Data and Information Quality - Dimensions, Principles and Techniques (Hardcover, 1st ed. 2016)
Loot Price: R4,369
Discovery Miles 43 690
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Data and Information Quality - Dimensions, Principles and Techniques (Hardcover, 1st ed. 2016)
Series: Data-Centric Systems and Applications
Expected to ship within 12 - 17 working days
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This book provides a systematic and comparative description of the
vast number of research issues related to the quality of data and
information. It does so by delivering a sound, integrated and
comprehensive overview of the state of the art and future
development of data and information quality in databases and
information systems. To this end, it presents an extensive
description of the techniques that constitute the core of data and
information quality research, including record linkage (also called
object identification), data integration, error localization and
correction, and examines the related techniques in a comprehensive
and original methodological framework. Quality dimension
definitions and adopted models are also analyzed in detail, and
differences between the proposed solutions are highlighted and
discussed. Furthermore, while systematically describing data and
information quality as an autonomous research area, paradigms and
influences deriving from other areas, such as probability theory,
statistical data analysis, data mining, knowledge representation,
and machine learning are also included. Last not least, the book
also highlights very practical solutions, such as methodologies,
benchmarks for the most effective techniques, case studies, and
examples. The book has been written primarily for researchers in
the fields of databases and information management or in natural
sciences who are interested in investigating properties of data and
information that have an impact on the quality of experiments,
processes and on real life. The material presented is also
sufficiently self-contained for masters or PhD-level courses, and
it covers all the fundamentals and topics without the need for
other textbooks. Data and information system administrators and
practitioners, who deal with systems exposed to data-quality issues
and as a result need a systematization of the field and practical
methods in the area, will also benefit from the combination of
concrete practical approaches with sound theoretical formalisms.
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