Principles of Data Integration Cover

Principles of Data Integration

ISBN/ASIN: 9780124160446 | 2012 | pdf | 520/484 pages | 11.8 Mb
Publisher: Morgan Kaufmann | Author: Doan, AnHai (Auth.)

"This is the definitive book on data integration technology, written by experts who invented muchof the technology they write about. It’s comprehensive, with lots of technical detail very clearly explained. It’s a must-read for anyone involved in the development of data integration solutions."–Philip A. Bernstein, Distinguished Scientist, Microsoft Corporation"Despite having been with us for decades, data integration remains a challenging, multi-faceted problem. This book does an excellent job of bringing together and explaining its many facets along with the technical solutions that have been developed to date. The authors are three of the field's leading contributors, with a mix of both academic and industrial experience, and their presentation includes examples and manages to make even the more theoretical material accessible to readers. All aspects of modern data integration are covered, including different styles of integration, data and schema matching, query processing and wrappers, as well as challenges posed by the Web and the wide variety of data types and formats that must be integrated today. This book should be a great resource for graduate courses on data integration."–Michael Carey, Bren Professor of Information and Computer Sciences, UC Irvine"The days of enterprises/organizations depending on a single, closed database have given way to a Web-dominated world in which multiple databases must interoperate and integrate. Doan (computer science, U. of Wisconsin, Madison) and colleagues at Google and the University of Pennsylvania address how database ideas have broadened to accommodate external sources of structured information, distributed aspects of the Web, and issues of data-sharing. Part I treats topics and techniques for data queries, integration, and warehousing covered in a database course. Part II discusses extended data representations that capture properties not present in the standard relational data model. Then they present novel architectures for, and trends in, addressing specific integration problems, e.g., of Web sources. Includes an extensive bibliography."–Reference and Research Book News, October 2012

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