Editors:
- Presents a comprehensive framework based on organizational, architectural, and computational techniques and solutions
- Includes a separate section devoted to successful data quality approaches in industry
- Combines contributions from leading researchers, recognized industry thought leaders, and experienced practitioners
- Includes supplementary material: sn.pub/extras
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Table of contents (17 chapters)
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Front Matter
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Organizational Aspects of Data Quality
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Front Matter
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Architectural Aspects of Data Quality
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Front Matter
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Computational Aspects of Data Quality
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Front Matter
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Data Quality in Action
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Front Matter
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About this book
The issue of data quality is as old as data itself. However, the proliferation of diverse, large-scale and often publically available data on the Web has increased the risk of poor data quality and misleading data interpretations. On the other hand, data is now exposed at a much more strategic level e.g. through business intelligence systems, increasing manifold the stakes involved for individuals, corporations as well as government agencies. There, the lack of knowledge about data accuracy, currency or completeness can have erroneous and even catastrophic results.
With these changes, traditional approaches to data management in general, and data quality control specifically, are challenged. There is an evident need to incorporate data quality considerations into the whole data cycle, encompassing managerial/governance as well as technical aspects.
Data quality experts from research and industry agree that a unified framework for data quality management should bring together organizational, architectural and computational approaches. Accordingly, Sadiq structured this handbook in four parts: Part I is on organizational solutions, i.e. the development of data quality objectives for the organization, and the development of strategies to establish roles, processes, policies, and standards required to manage and ensure data quality. Part II, on architectural solutions, covers the technology landscape required to deploy developed data quality management processes, standards and policies. Part III, on computational solutions, presents effective and efficient tools and techniques related to record linkage, lineage and provenance, data uncertainty, and advanced integrity constraints. Finally, Part IV is devoted to case studies of successful data quality initiatives that highlight the various aspects of data quality in action. The individual chapters present both an overview of the respective topic in terms of historical research and/or practice and state of the art, as well as specific techniques, methodologies and frameworks developed by the individual contributors.
Researchers and students of computer science, information systems, or business management as well as data professionals and practitioners will benefit most from this handbook by not only focusing on the various sections relevant to their research area or particular practical work, but by also studying chapters that they may initially consider not to be directly relevant to them, as there they will learn about new perspectives and approaches.
Reviews
From the reviews:
“The book is suitable for academics and students in computer science, information systems, and management. Practitioners should find matters related to their practice areas in one division or another. … This book goes a long way toward providing an integrative view of data quality, and is a useful addition to the body of literature in this area.” (R. M. Malyankar, Computing Reviews, May, 2014)Editors and Affiliations
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University of Queensland, Brisbane, Australia
Shazia Sadiq
About the editor
Bibliographic Information
Book Title: Handbook of Data Quality
Book Subtitle: Research and Practice
Editors: Shazia Sadiq
DOI: https://doi.org/10.1007/978-3-642-36257-6
Publisher: Springer Berlin, Heidelberg
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2013
Hardcover ISBN: 978-3-642-36256-9Published: 23 May 2013
Softcover ISBN: 978-3-642-44184-4Published: 20 June 2015
eBook ISBN: 978-3-642-36257-6Published: 13 August 2013
Edition Number: 1
Number of Pages: XII, 438
Topics: Database Management, Information Storage and Retrieval, Management of Computing and Information Systems, Data Structures and Information Theory, Business IT Infrastructure