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Data Modeling Essentials, Third Edition provides expert tutelage for data modelers, business analysts and systems designers at all levels. Beginning with the basics, this book provides a thorough grounding in theory before guiding the reader through the various stages of applied data modeling and database design. Later chapters address advanced subjects, including business rules, data warehousing, enterprise-wide modeling and data management.
The third edition of this popular book retains its distinctive hallmarks of readability and usefulness, but has been given significantly expanded coverage and reorganized for greater reader comprehension. Authored by two leaders in the field, Data Modeling Essentials, Third Edition is the ideal reference for professionals and students looking for a real-world perspective.
� Thorough coverage of the fundamentals and relevant theory.
� Recognition and support for the creative side of the process.
� Expanded coverage of applied data modeling includes new chapters on logical and physical database design.
� New material describing a powerful technique for model verification.
� Unique coverage of the practical and human aspects of modeling, such as working with business specialists, managing change, and resolving conflict.
� Extensive online component including course notes and other teaching aids (www.mkp.com).
UML diagrams now available! Visit the companion site for more details.
Click here to view a book review by Steve Hoberman!
- Sales Rank: #523806 in Books
- Published on: 2004-11-18
- Original language: English
- Number of items: 1
- Dimensions: 9.25" h x 1.27" w x 7.50" l, 2.47 pounds
- Binding: Paperback
- 560 pages
Review
"The perfect balance of theory and practice, giving the reader both the foundation and the tools to deliver high-quality data models."
-Karen Lopez, Principal, InfoAdvisors, Inc.
"The complete guide to data modeling for the reflective practitioner. Students like this book and so do I -- it is clear and accessible without sacrificing rigor."
-Professor Graeme Shanks, School of Business Systems, Monash University, Australia
"A unique, practical and comprehensive guide, providing an invaluable resource to anyone involved in data modeling from the novice to the expert data modeler."
-Len Silverston, author of The Data Model Resource Book, Volumes 1 and 2.
"Includes an extraordinary amount of good, useful, and well articulated information about the field."
-David Hay, President, Essential Strategies, Inc. and author of Data Model Patterns
"Data Modeling Essentials is a fresh look at an old topic...much more accesible and refreshing in its tone and attitude. Simsion's explanations are very clear and his examples easy to follow...This book is useful for both beginners and experienced data modelers who want a new innovative approach to the important task of documenting data requirements." - The Bridge --Barbara A. Carkenord
"The book is extremely well-written. It is humorous at times, full of useful anecdotes, and follows a very logical sequence...In summary, I found Data Modeling Essentials, Third Edition, very useful for data modelers at any level of experience." - DM Review
From the Back Cover
Data Modeling Essentials, Third Edition provides expert tutelage for data modelers, business analysts and systems designers at all levels. Beginning with the basics, this book provides a thorough grounding in theory before guiding the reader through the various stages of applied data modeling and database design. Later chapters address advanced subjects, including business rules, data warehousing, enterprise-wide modeling and data management.
The third edition of this popular book retains its distinctive hallmarks of readability and usefulness, but has been given significantly expanded coverage and reorganized for greater reader comprehension. Authored by two leaders in the field, Data Modeling Essentials, Third Edition is the ideal reference for professionals and students looking for a real-world perspective.
Features
� Thorough coverage of the fundamentals and relevant theory.
� Recognition and support for the creative side of the process.
� Expanded coverage of applied data modeling includes new chapters on logical and physical database design.
� New material describing a powerful technique for model verification.
� Unique coverage of the practical and human aspects of modeling, such as working with business specialists, managing change, and resolving conflict.
� Extensive online component including course notes and other teaching aids (www.mkp.com).
About the Author
Graeme C. Simsion has over 25 years experience in information systems as a DBA, data modeling consultant, business systems designer, manager, and researcher. He is a regular presenter at industry and academic forums, and is currently a Senior Fellow with the Department of Information Systems at the University of Melbourne.
Graham C. Witt is an independent consultant with over 30 years of experience in assisting enterprises to acquire relevant and effective IT solutions. His clients include major banks and other financial institutions; businesses in the insurance, utilities, transport and telecommunications sectors; and a wide variety of government agencies. A former guest lecturer on Database Systems at University of Melbourne, he is a frequent presenter at international data management conferences.
Most helpful customer reviews
42 of 44 people found the following review helpful.
A classic for all data professionals
By Karen Lopez
Simsion and Witt's _Data Modeling Essentials_ has been a classic on my data management bookshelf since the first edition. Now in the 3rd Edition, this work has become even more valuable and useful on data management projects. The fact that the authors continue to enhance and expand their work is a real asset.
This work is targeted at both students and experienced information technology professionals.
...and, of course, any data modeling book that manages to quote from Led Zeppelin's "Stairway to Heaven", Stephen Covey's _7 Habits of Highly Effective People_, Bob Dylan's "Brownsville Girl", and even Jack Kerouac must be a good read, right?
Let's start with what I really like about this book:
1) _Essentials_ starts at the beginning "What is a Data Model" and works its way through entities, attributes, subtypes, ERDs, normalization and all the basics through to fairly advanced topics such as the use of surrogate keys, transformations, designing for performance, time dependence and advanced normalization. Simsion and Witt make this trek in a balanced and clearly-explained manner. This is no _...For Dummies_ type work - it is a true professional level book that consistently targets the whys, why-nots, how-much and when-to-stops of data modeling.
2) Along the way, the authors refer to multiple methods, notations, and tools, while sticking with a single notation throughout. I much prefer data modeling books like _Essentials_ that use the most common notation in modeling, as these books are more useful in a variety of contexts over those that use more obscure notations. I can see how this edition has updated references to tool features and modeling support.
3) _Essentials_ includes discussions that are, more often than not, left out of technical works in the data management field. For instance, most of the topics include references to myths, trade-offs, and real world issues. The authors' willingness to explore these topics is, in my opinion, a sign of maturity of this book. So many technical texts in database design completely ignore the trade-offs in tuning, simplifying design, and working with external constraints, etc., but the authors jump right in and give their opinions on what is best.
4) This book contains a substantial amount of material on the development of physical models and databases. Many data modeling books treat this area lightly and I find the authors' thoroughness in this area a really strength. Many logical data modelers struggle with turning beautiful designs into working databases and _Essentials_ does a great job of explaining the trade offs in a non-DBMS-specific manner.
This 3rd edition expands in these areas to become a true professional's guide to data modeling.
What I didn't like about Essentials:
1) While the majority of the work uses contemporary terminology and notation, there are still some terms with currency issues. For instance, when describing process models, the examples use Data Flow Diagramming notation, something that is not quite a common as it used to be and can be perceived as dated. On the other hand, what did the authors choose to call the boxes on a data model? "Entity Classes", in deference to what object modelers chose to call these boxes. The authors believe that this deference will improve communications between modelers. I don't agree. Having borrowed a term from the object crowd, how does the book refer to modelers? "E-R modelers", a term that is rare and dated. And in many places, instead of referring to data models, they are called "E-R models". Data modeling tools are referred to as "documentation tools" or "CASE tools" - these are also dated terms. Perhaps in the 4th edition we will see a complete updating of terminologies and notations.
2) As a textbook, this work recommends approaches that are not suitable for novice modelers. For instance, the authors recommend the use of dummy rows and special dummy words in databases to avoid Nulls, the use of multi-valued attributes (not columns, attributes), etc. Of course these things happen in the real world, but to recommend them in a text without sufficiently covering the down sides of these approaches is going to get a few newbie modelers in hot water.
3) As a professional guide, the definition of "Logical Model" as a model that is DBMS-specific is not a well-accepted definition and will cause confusion when professionals work with others who define a Logical Model as a model that is DBMS-independent.
4) I believe that the introduction of Normalization in Chapter 2 is premature. Many normal forms can be `met' by following good modeling practices. If these practices were introduced in an appropriate manner, the authors could then show how these practices support normalization.
5) As I have said in reviews of other data modeling works, I hold text book examples to a higher standard. _Essentials_ uses an entity and relationship naming standard that is overly prone to errors and misunderstandings: infinitive-based verb phrases with a "be" form in the reverse relationship. This leads unfortunately weak relationship names, such as those in figure 10.3 Insurance Model:
a. Policy Type may classify Policy / Policy must be classified by Policy Type (using may and must based on optionality)
b. Policy must involve Person Role in Policy / Person Role in Policy must be for Policy
I'm not sure how to interpret these. Why is "involve" the reverse of "be for"? What does the term "be for" really mean, anyway? What does "be of" mean?
What if I don't want to introduce cardinality in my business sentences? I'd get sentences such as "Person Role in Policy be for Policy". What business user wants to work with a model that has assertions such as that? What does the relationship that is named "nominate" on one side and "be party to" on the other really mean? This sounds like I may just be nitpicking, but I continue to find this be-form and infinitive verb style prone to errors and I wish authors would give up on it in textbooks. If the authors can't make it work, how will the students?
Overall
While I've mentioned a handful of things I didn't like in this work, I still highly recommend it. I especially appreciate the approach to topics that most authors shy away from. This is a substantial work - it has goodies for new modelers, intermediate modelers, and advanced modelers. _Data Modeling Essentials_ is my number one recommended how-to data modeling book. It is the perfect balance of theory and practice, giving the reader both the foundation and the tools to deliver high-quality data models.
Disclaimer: I was a pre-publication reviewer for this work and received compensation, including copy of the book, for providing a review based on my data modeling experience. I receive no compensation from the publisher related to sales or promotion of this book.
0 of 0 people found the following review helpful.
Great for experienced modelers but I pity any beginners
By William Talada
This is an old book from 2004 but still very relevant today. I read 200 pages yesterday and really enjoyed it. It is good to see that some best practices that I've stumbled into are validated in the book. This really is a must-have book if you do data modeling and possibly is the only one you need.
The book was mostly understandable, given my decades of database experience but there were still plenty of large paragraphs that were so filled with new abstract terms and vagueness that I'm sure only the author himself understood what was being said. There are very few concrete examples and practical walk-throughs that I pity any college student who might be trying to understand this stuff.
0 of 0 people found the following review helpful.
Five Stars
By Ankur Gupta
Very helpful
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