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Information Modeling and Relational Databases: From Conceptual Analysis to Logical Design Hardcover – Illustrated, 10 April 2008
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Information Modeling and Relational Databases, Second Edition, provides an introduction to ORM (Object-Role Modeling)and much more. In fact, it is the only book to go beyond introductory coverage and provide all of the in-depth instruction you need to transform knowledge from domain experts into a sound database design. This book is intended for anyone with a stake in the accuracy and efficacy of databases: systems analysts, information modelers, database designers and administrators, and programmers.
Terry Halpin, a pioneer in the development of ORM, blends conceptual information with practical instruction that will let you begin using ORM effectively as soon as possible. Supported by examples, exercises, and useful background information, his step-by-step approach teaches you to develop a natural-language-based ORM model, and then, where needed, abstract ER and UML models from it. This book will quickly make you proficient in the modeling technique that is proving vital to the development of accurate and efficient databases that best meet real business objectives.
- ISBN-100123735688
- ISBN-13978-0123735683
- Edition2
- PublisherMorgan Kaufmann
- Publication date10 April 2008
- LanguageEnglish
- Dimensions19.05 x 3.81 x 24.13 cm
- Print length976 pages
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About the Author
Dr. Tony Morgan is a British computer scientist, data modeling consultant, and Professor in Computer Science at INTI International University, Malaysia. Dr. Morgan obtained his BA in Earth Sciences from The Open University, his BSc in Computer Systems Engineering from Coventry University, where in 1984 he also obtained his MSc in Control Engineering. In 1988 he obtained his PhD in Computer Science from University of Cambridge with a thesis on automated decision-making using qualitative reasoning. Dr. Morgan has done extensive work in industry with companies such as Unisys, EDS, and other corporations across transport, aerospace, government, and financial services, including the UK’s National Computing Centre in Manchester. Dr. Morgan has published several articles on AI and simulation. In 2003 he was appointed Professor of Computer Science and Vice President of Enterprise Informatics at Neumont University, Utah, USA. His research interests focus on business rules and business processes and the rapid development of high-quality information systems. Along with Dr. Halpin, he is the co-author of Information Modeling and Relational Databases, Second Edition, Elsevier/Morgan Kaufmann.
Product details
- Publisher : Morgan Kaufmann; 2 edition (10 April 2008)
- Language : English
- Hardcover : 976 pages
- ISBN-10 : 0123735688
- ISBN-13 : 978-0123735683
- Dimensions : 19.05 x 3.81 x 24.13 cm
- Best Sellers Rank: 198,667 in Books (See Top 100 in Books)
- Customer Reviews:
About the authors
Terry Halpin, BSc, DipEd, BA, MLitStud, PhD, is a Principal Scientist at LogicBlox (headquartered in Atlanta), and a Professor in computer science at INTI International University, Malaysia. He has held senior faculty positions at Australian and American universities, and worked on data modeling technology for several companies including Microsoft Corporation. He has authored over 160 technical publications and six books, is a regular columnist for the Business Rules Journal, and is a recipient of the DAMA International Achievement Award for Education and the IFIP Outstanding Service Award. His personal interests include martial arts, body surfing, philosophy, and fantasy novels.
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a Fire HDX every diagram is so small that it has to be zoomed to
read it. The good news is that when zoomed the text is only slightly
blurred.
The book has more typos than I would like, but no more than most
modern textbooks.
As for the content, I first met this database design method on an
MSc course. At the time it struck me as being sensible, effective,
and the right way to do the job. 25 years later, I still think it's
the right way to design a database.
The book describes clearly how to design a database and, just as
important, why it is done that way. For the most part it is very
straightforward and simple. There are programs, some free, that do
the final more complicated step of turning the design into a set of
relational database tables. These are guaranteed to be in 5th normal
form (highly desirable).

Back in the University, when taught UML and ER diagrams, I was always a bit skeptic about all of them, as I could never really fit them into one big picture. This book was a great aid to me in this regard: not only does it cover fact-oriented information modeling (rooted in logic -- and so, making sense!), but it also shows the path to implementation (which most certainly will make use of relational databases available on the market), thereby bridging the disconnect mentioned above.
With this book, one can learn:
- an approach to systematically modelling "the real world" (that is, finding out which facts a given business is interested in, and finding how these facts are related to each other) with an eye towards implementation
- how some of the existing information modeling methods (e.g., UML, ER, IDEFx, ORM) can express same concepts, with a comparative analysis of the benefits and drawbacks of each method (personally, this is something I enjoy very much)
There are no necessary prerequites to reading (the book starts lightly), however I think it would be best to become familiar with basic formal logic concepts beforehand, so as to have some familiarity with certain technicalities (such as a brief discussion of consistency of universe of discourse), thus not having to take detours while reading.


I feel like I have been warped back to 1989 when reading this book. Although there are some theoretical benefits to the approaches taken in the book, industry has largely chosen to not use many of the topics preached within. In the forwards it was mentioned that common industry modeling techniques were contrasted fairly (e.g. UML/ER) -- but I did not find this to be true. The book reads like a desperate attempt to make a lesser used modeling technique relevant. I was hopeful when picking up this book it would be a fair comparison and add a powerful tool I could use in my daily work data-modeling.
As a text-book for first-time data modelers this book does provide some value. Unfortunately, the explanations are dry, patronizing on simple topics and skip detail on complex ones. A typical explanation in the book reads: "For brevity, relational style assumes that variables in the rule head are universally quantified and that variables introduced in the body are existentially quantified." The examples are too simplistic to actually fully explain concepts - and frustratingly seem to avoid all real-world pitfalls we typically encounter as data modelers. On the positive side, if you have no background in modeling at all - you will learn something from this book.
For everyone else, this book is only useful if you are looking for a history lesson on alternative modeling approaches or need a different perspective than is offered in books focused on UML.
In the end, I think there are better choices for learning.