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.

Autorentext
AnHai Doan, Associate Professor in Computer Science at the University of Wisconsin-Madison. Consulting work with Microsoft AdCenter Lab and Yahoo Research Lab. Head of the Structured Data Group, Google Research, Mountain View, California. He joined Google in 2005 with the acquisition of his company, Transformic.Associate Professor at the University of Pennsylvania and a Faculty Member of the Penn Center for Bioinformatics. He received his PhD from the University of Washington. His research interests include data integration, data sharing among autonomous and heterogeneous systems, heterogeneous sensor networks, and information provenance and authoritativeness.

Klappentext
Data integration is the problem of answering queries that span multiple data sources (e.g., databases, web pages). Data integration problems surface in multiple contexts, including enterprise information integration, query processing on the Web, coordination between government agencies and collaboration between scientists. In some cases, data integration is the key bottleneck to making progress in a field. For example, when two companies merge, the number of different databases scattered across a company could easily reach 100. Obtaining a complete and organized view of data requires the application of data integration technology (i.e., semantic integration involves resolving the inevitable differences in certain concepts and definitions in their respective schemas, like "earnings," "compliant," etc. This book presents a comprehensive treatment of the issues faced in integrating data from multiple sources, from the theoretical principles to system issues and current challenges raised by the World Wide Web and cloud computing. It allows readers to answer the constantly recurring question: How do I approach answering queries when my data is stored in multiple databases that were designed independently by different people?

Zusammenfassung
Provides an introduction to the theory and concepts underlying data integration techniques, with detailed, instruction for their application using concrete examples throughout to explain the concepts. This title also provides a working knowledge of data integration concepts and techniques.

Inhalt

CH 1: Introduction

Part I: Foundational Data Integration Techniques

CH 2: Manipulating Query Expressions

CH 3: Describing Data Sources

CH 4: String MatchingCH 5: Schema Matching and Mapping

CH 6: General Schema Manipulation Operators

CH 7: Data Matching

CH 8: Query Processing

CH 9: Wrappers

CH 10: Data Warehousing and Caching

Part II: Integration with Extended Data Representations

CH 11: XML

CH 12: Ontologies and Knowledge Representation

CH 13: Incorporating Uncertainty into Data Integration

CH 14: Data Provenance

Part III: Novel Integration Architectures

CH 15: Data Integration on the Web

CH 16: Keyword Search: Integration on Demand

CH 17: Peer-to-Peer Integration

CH 18: Integration in Support of Collaboration

CH 19: The Future of Data Integration