Principles of Data Integration

Principles of Data Integration is the first comprehensive textbook of data integration, covering theoretical principles and implementation issues as well as current challenges raised by the semantic web and cloud computing. The book offers a range of data integration solutions enabling you to focus on what is most relevant to the problem at hand. Readers will also learn how to build their own algorithms and implement their own data integration application.

Written by three of the most respected experts in the field, this book provides an extensive introduction to the theory and concepts underlying today's data integration techniques, with detailed, instruction for their application using concrete examples throughout to explain the concepts.

This text is an ideal resource for database practitioners in industry, including data warehouse engineers, database system designers, data architects/enterprise architects, database researchers, statisticians, and data analysts; students in data analytics and knowledge discovery; and other data professionals working at the R&D and implementation levels.

• Offers a range of data integration solutions enabling you to focus on what is most relevant to the problem at hand
• Enables you to build your own algorithms and implement your own data integration applications

Alon Halevy, Head of the Structured Data Management Research group at Google. Prior to that, he was a professor of Computer Science at the University of Washington in Seattle, where he founded the database group. In 1999, Dr. Halevy co-founded Nimble Technology, one of the first companies in the Enterprise Information Integration space.  In 2004, he founded Transformic Inc., a company that created search engines for the deep web, and was acquired by Google. Dr. Halevy is a Fellow of the Association for Computing Machinery.


Zachary Ives, Associate Professor at the University of Pennsylvania and a Faculty Member of the Penn Center for Bioinformatics.  His research interests include data integration and sharing, data-centric computation, sensor networks, and data provenance and authoritativeness. He has been awarded the Christian R. and Mary F. Lindback Foundation Award for Distinguished Teaching.