Synopses & Reviews
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.
"Database Modeling and Design
is one of the best books that I have seen for explaining how to build database applications. The book is informative, well-written, and concise."-Michael Blaha, DSc., Consultant, Modelsoft Consulting Corp
"This book book is by far the best book available on classic database design. Topics like normalization and many-to-many and n-ary association semantics are without peer in teaching you how to model real-world complexities. This latest edition extends the classic material with extensive discussion of modern tools and other aspects of logical database design. Every database architect should have this book at hand."-Bob Muller, Data Analyst, Poesys Associates
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.
The database professional's only complete business intelligence guide to data modeling concepts and logical database design.
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 fifth 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.
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.
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.
Univ of Mich, Ann Arbor (EE/CS dept)
Table of Contents
2. The Entity-Relationship Model
3. Unified Modeling Language (UML)
4. Requirements Analysis and Conceptual Modeling
5. Transforming the Conceptual Data Model to SQL
7. An Example of Logical Database Design
8. Object Relational Design
9. XML and Web Databases
10. Business Intelligence
11. CASE Tools
Appendix: The Basics of SQL