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

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9780126853520: Database Modeling and Design: Logical Design (The Morgan Kaufmann Series in Data Management Systems)

Database systems and database design technology have undergone significant evolution in recent years. The relational data model and relational database systems dominate business applications; in turn, they are extended by other technologies like data warehousing, OLAP, and data mining. How do you model and design your database application in consideration of new technology or new business needs? In the extensively revised fourth edition, you'll get clear explanations, lots of terrific examples and an illustrative case, and the really practical advice you have come to count on - with design rules that are applicable to any SQL-based system. But you'll also get plenty to help you grow from a new database designer to an experienced designer developing industrial-sized systems; a detailed look at the Unified Modeling Language (UML-2) as well as the entity-relationship (ER) approach for data requirements specification and conceptual modeling - with examples throughout the book in both approaches; the details and examples of how to use data modeling concepts in logical database design, and the transformation of the conceptual model to the relational model and to SQL syntax; the fundamentals of database normalization through the fifth normal form; practical coverage of the major issues in business intelligence - data warehousing, OLAP for decision support systems, and data mining; examples for how to use the most popular CASE tools to handle complex data modeling problems; and, exercises that test understanding of all material, plus solutions for many exercises.

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Review:

"An explicit presentation on Business Intelligence is a major strength of this book. For beginners, there is an elegant presentation on SQL in the appendix and the book is supplemented by a detailed glossary. Exercises, examples and solutions constitute an important part of this book. This book is useful reading for both beginners and advanced users as the contents integrate elements that would address various audiences at different levels." - P. Pichappan, Department of Information Science, Annamalai University, India

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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