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

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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.
+ Exercises that test understanding of all material, plus solutions for many exercises.

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

I also am a reviewer of the book and an interested colleague. I've used this book since its first edition as my main reference on basic data modeling, and I have been happy to comment on its newer editions. This 4th edition improves on earlier ones by including the Unified Modeling Language (UML), my own first choice for a design language for data modeling. The chapter on the UML includes everything you need, but it keeps it as simple and straightforward as possible, making the material very accessible. The real contribution of the book is in the normalization chapter and in the excellent description and examples of n-ary relationships and the consequences of their multiplicities, a very-hard-to-understand corner of the data modeling world. The inclusion in this edition of material on OLAP and data warehousing is also welcome, though very limited in scope. Finally, moving the physical design material into a separate book makes this book much more cohesive and useful as a reference for data modeling.

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