Enterprise Model Patterns: Describing the World (UML Version)

If you are in any way involved in software development in the business world, then you owe it to yourself to add this title to your collection.If you don't know David Hay, he wrote the definitive work on data model patterns 15 years ago with Data Model Patterns: Conventions of Thought. My introduction to that book was nothing short of revolutionary as it fundamentally changed the way I thought about data modeling and systems development. Enterprise Model Patterns continues the legacy with the same clear, concise thinking (as well as the footnotes) that made Data Model Patterns a classic.Whenever you start a modeling effort, you should turn to Mr. Hay for inspiration, insight, and solutions to common modeling challenges. You don't have to reinvent the wheel. Instead, leverage Mr. Hay's expertise and years of hands-on experience across multiple industries. He thinks the right way. He gets it. You can feel it as you read that you're on the right track to creating flexible, stable, and robust models.If you can wrap your brain around Chapter 9 - The Template (most of which is available online via Amazon's preview), then you're well on your way to modeling nirvana as the concepts are universally applicable to just about any domain.A note about the 'UML Version': if you (like me) were initially turned off by the choice of UML, then put aside your fears. Really. It was a completely painless, quick, and easy transition. Mr. Hay reviews the notation in the introduction and it then becomes a non-issue (as the strength of the book is the patterns (and the thinking behind the patterns) and not the notation).My copy is only a few weeks old and it's already dog-eared and well worn, signs of a great reference.

Very well written. The data modeling revolution has been 30 years in the making but its time has finally come. Everyone that knows what's going on realizes that quality software can only be built on the solid foundation of good data models.

David Hay does it again with a solid, comprehensive set of enterprise models, complete with a good overview of his design and modeling philosophy and how his syntactically rigorous, patterned, approach leads to clearer, more useful, flexible models and provide a better communication tool for communication between IT and the business. Just looking at the dominant data modeling tools, with their inflexible and confusing coat-hanger sub-type notation, one could say Hay has lost the argument, but his book is the best rebuttal to ugly, spaghetti models those tools produce and, with his adoption of the customized UML-tool adaptation he suggests, may still prevail. Bravo David.

The awesome useful book, like any other by David Hay. Besides the data models, I learned something about the business domains they describe A must read and use as a reference for any business analyst or real-world data model designer. It is so nice of Amazon to make the Kindle version available for a fraction of the price for those who purchased the print edition.

I learned both Data modeling and Zachman framework by reading this book. I recommended this to all my colleagues. and my colleagues also think this book is good and bought their own copies.

I find this enterprise model patterns book an indispensable tool, and tout it at all opportunities. It is a compendium of experience, wisdom, and reusable patterns, and an excellent tutorial.When I first looked though, I thought, as many with long experienced might, was "well, I know all this, and have done even better models of many of these things, so what's new?". Over time, I realized that what is **new** is putting it all together, and including so many insights and observations from David Hay's deep experience, that begins to represent a foundation for a serious and deep profession.Yet in practice, in most standard software engineering environments, UML versus an E/R modelling language, has been a huge, meaningless non-issue that puts up artificial barriers to success. This work begins to break down that roadblock, and help make clear that the language in which a model is created is a mostly separate matter from what is modeled. Especially in a day when their are tools that map between these languages, and between these and OWL, for example.More broadly, I find that there is so much overlap and lack of coordination, between so many things in computer science and engineering, from metadata management to enterprise architecture to ontology, to model driven development, with so much tunnel vision, even among these interests that *all" profess to be looking at "the big picture," that it is hard for me to get people in any of these other fields to take into account what David Hay done here, which is a start at pulling together some of the threads.In fact, my only complaint is that this profession is called in the book, and by other reviewers "data modelling", even though the title is Enterprise Model Patterns. This makes it seem somewhat more retrospective than it is. I complain about this because:1. Most people identify *data* modelling with what is in a database. But the same information, with the same relationships, must appear in user interfaces, messages, process specifications, component contracts, web data relationships, and as parts of shared industry ontologies. This book could help all of these endeavors, and help productivity if the people engaged in them were able to separate the important ideas from the technological environment. In no other engineering field is there so much decade over decade reinventions, as technology changes.2. David Hay defines an enterprise data model to be "An E/R Model whose domain is an entire business or government agency". But entire domains of human endeavor, such as money transfer, organic chemistry, the practice of information modelling itself, securities clearance, need these kinds of models, and in today's interconnected world, they are sorely needed. So, to me, it is somewhat narrow to see the focus on single businesses. (Especially as the book itself shows that there are patterns that apply to entire domains of human endeavor.

It good