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Journey to Data Quality
(2006)
Yang W. Lee, Leo L. Pipino, James D. Funk, Richard Y. Wang
All organizations today confront data quality problems, both systemic
and structural. Neither ad hoc approaches nor fixes at the systems
level--installing the latest software or developing an expensive data
warehouse--solve the basic problem of bad data quality practices.
Journey to Data Quality offers a roadmap that can be used by
practitioners, executives, and students for planning and implementing
a viable data and information quality management program. This practical
guide, based on rigorous research and informed by real-world examples,
describes the challenges of data management and provides the principles,
strategies, tools, and techniques necessary to meet them.
The authors, all leaders in the data quality field for many years,
discuss how to make the economic case for data quality and the importance
of getting an organization's leaders on board. They outline different
approaches for assessing data, both subjectively (by users) and objectively
(using sampling and other techniques). They describe real problems and
solutions, including efforts to find the root causes of data quality
problems at a healthcare organization and data quality initiatives taken
by a large teaching hospital. They address setting company policy on data
quality and, finally, they consider future challenges on the journey to
data quality.
(available at The MIT Press,
ICIQ Conference Discount Coupon,
also discount at amazon.com
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Introduction to Information Quality
(1st ed. 2006)
Craig Fisher, Eitel Lauria, Shobha Chengular-Smith, Richard WangTable of Contents [PDF]
This book will educate
people about the critical issues in data and information quality that have
been plaguing information systems for many years. Researchers have only
recently begun to address data quality as a discipline in its own right,
and a body of data quality literature has just begun to appear.
Researchers at Massachusetts Institute of Technology (MIT) began a total
data quality management program and have hosted ten international
conferences on information quality aimed at practitioners, academicians,
and researchers. This book is built on two primary sources. After an
extensive literature review and study, an importance of data quality
knowledge and skills survey was completed by 110 data quality researchers
and practitioners, all data quality leaders in their own right, at the
International Conference on Information Quality held at MIT. The results
of these studies led to a consensus of the most critical skills necessary
to begin performing information quality work. An introduction to those
critical skills and knowledge areas are the primary topics of this book.
The second source is the research into data and information quality of the
four authors who collectively have published over 100 articles.
Copies are available at the online Authorhouse Bookstore, through their Channel Book Sales Department hotline at 888.728.8267 Ext. 5022, or by email to bkorders@authorhouse.com.
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Information Quality
(2005)
A special volume in the
Advances
in Management Information Systems monograph series.
Editors: Richard Wang, Elizabeth Pierce, Stuart Madnick,
and Craig Fisher
(Available
at Amazon.com)
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Quality Information and Knowledge
(1999)
Kuan-Tsae Huang, Yang W. Lee, Richard Y. Wang
Three leaders in
intellectual capital management, Dr. Kuan-Tsae Huang, Professor
Yang W. Lee, and Professor Richard Y. Wang, show how information
can be assessed, evaluated, managed, and promulgated to make your
businesses more responsive, efficient,
and effective. They illustrate their ideas with
real-world examples of companies that have faced
million-dollar losses due to poor data management, as well as
industry leaders who have prospered through Total Data Quality
Management.
(Available at Amazon.com)
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Data Quality
(2001)
Richard Y. Wang, Mostapha Ziad, Yang W. Lee
An expose of research and
practice in data quality for technically-oriented researchers,
Ph.D candidates and IT professionals. Offers insights into the
theoretical areas of data quality and the application of key
concepts.
(Available at
Amazon.com and
Kluwer) |
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