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Database Modeling and Design: Logical Design (The Morgan Kaufmann Series in Data Management Systems) - Softcover

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Synopsis

Database Modeling and Design, Fifth Edition, focuses on techniques for database design in relational database systems.

This extensively revised fifth edition features clear explanations, lots of terrific examples and an illustrative case, and practical advice, with design rules that are applicable to any SQL-based system. The common examples are based on real-life experiences and have been thoroughly class-tested.

This book is immediately useful to anyone tasked with the creation of data models for the integration of large-scale enterprise data. It is ideal for a stand-alone data management course focused on logical database design, or a supplement to an introductory text for introductory database management.

  • In-depth detail and plenty of real-world, practical examples throughout
  • Loaded with design rules and illustrative case studies that are applicable to any SQL, UML, or XML-based system
  • Immediately useful to anyone tasked with the creation of data models for the integration of large-scale enterprise data

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From the Back Cover

Database systems and database design technology have seen significant changes in recent years. The relational data model and relational database systems dominate applications; in turn, they are extended by other technologies like data warehousing, OLAP, and data mining. Businesses are expanding and require well-constructed databases to track their new and various needs. How do you model and design your database application in the event of new technology or new business needs?

The answers are all in the fifth edition of Database Modeling and Design: Logical Design. This book shows you how to develop data modeling concepts and logical database design consistently over a wide scope in a way that will support the needs of your enterprise. Updated clear explanations, in-depth detail, real-world examples, and illustrative case studies provide you with practical advice that you can count on―with design rules that are applicable to any SQL-based system.

NEW to this edition:

*NEW- A whole chapter devoted to XML and web databases. What you need to know to utilize XML rather than relational tables.

*A whole chapter describing Object Relational Design. Learn how to make a choice between what is in the database as a BLOB and what is outside in a separate file.

About the Author

Toby J. Teorey is a professor in the Electrical Engineering and Computer Science Department at the University of Michigan, Ann Arbor. He received his B.S. and M.S. degrees in electrical engineering from the University of Arizona, Tucson, and a Ph.D. in computer sciences from the University of Wisconsin, Madison. He was general chair of the 1981 ACM SIGMOD Conference and program chair for the 1991 Entity-Relationship Conference. Professor Teorey’s current research focuses on database design and data warehousing, OLAP, advanced database systems, and performance of computer networks. He is a member of the ACM and the IEEE Computer Society.

Sam Lightstone is a Senior Technical Staff Member and Development Manager with IBM’s DB2 product development team. His work includes numerous topics in autonomic computing and relational database management systems. He is cofounder and leader of DB2’s autonomic computing R&D effort. He is Chair of the IEEE Data Engineering Workgroup on Self Managing Database Systems and a member of the IEEE Computer Society Task Force on Autonomous and Autonomic Computing. In 2003 he was elected to the Canadian Technical Excellence Council, the Canadian affiliate of the IBM Academy of Technology. He is an IBM Master Inventor with over 25 patents and patents pending; he has published widely on autonomic computing for relational database systems. He has been with IBM since 1991.

Tom Nadeau is the founder of Aladdin Software (aladdinsoftware.com) and works in the area of data and text mining. He received his B.S. degree in computer science and M.S. and Ph.D. degrees in electrical engineering and computer science from the University of Michigan, Ann Arbor. His technical interests include data warehousing, OLAP, data mining and machine learning. He won the best paper award at the 2001 IBM CASCON Conference.

H.V. Jagadish is a professor in EE and CS at the University of Michigan, Ann Arbor, where he is part of the database group affiliated with the bioinformatics program and the Center for Computational Medicine and Bioinformatics. Prior to joining the Michigan faculty, he spent over a decade at AT&T Bell Laboratories as a research scientist where he became head of the Database division.

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  • PublisherMorgan Kaufmann
  • Publication date2011
  • ISBN 10 0123820200
  • ISBN 13 9780123820204
  • BindingPaperback
  • LanguageEnglish
  • Edition number5
  • Number of pages352
  • Rating
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