Rating: 
Summary: Buyer Beware-what a tease!
Review: First the content: Contains everything that is not taught in graduate school (been there), and everything that a data modeller needs know about data modelling.
Next the format: Consumerism at its worse! An incomplete template here, missing template there-a tease to lay out $400 for a complete set of templates (on top of the $100 plus for both volumes already laid out).
The conclusion: invest in volume 1 and familiarize yourself with the valuable concepts layed out there-save your money and TIME with volume 2.
Rating: 
Summary: A must read for any database designer!!!
Review: I have implemented these models in two different industries and have started to build XML schemas for several of the models. These books saved me months of design time and had a huge impact on the success of our project. If you are doing any database design you must read these books.
Rating:
Summary: Excellent Resource
Review: In addition to being an excellent resource for data modelers, this book will help managers, business analysts, and architects gain an understanding of various industries and integration challenges facing IT professionals. Len's concepts, insights, and models provide a valuable contribution to data architecture.
Rating:
Summary: Excellent Resource
Review: Len's concepts, insights and model provide a valuable contribution to data architecture. This is a must have to quick start of enterprise data modeling and/or data warehouse initiatives.
Rating:
Summary: Excellent Resource
Review: Len's concepts, insights, and models provide a valuable contribution to data and business architecture. This book will help managers, business analysts, architects and data analysts gain an understanding of various industries and integration challenges facing IT professionals.
Rating:
Summary: What a time saver and valuable resource!
Review: My copy of both volume 1 and volume 2 have been referenced so many times that they are tattered and worn, but such a valuable resource on all my projects. Whenever I contemplate a design, I first look at this book and, more often than not, I get ideas and best practices on ways to model the construct. I have successfully re-used designs from both volume 1 and 2 and have applied models from both of these books towards the modeling of many industries including distribution, manufacturing, telecommunications, health care, financial services and professional services. I have found that the models provided are very relevant, re-usable, and of very high quality. They also provide all the details necessary to create physical database designs. They include entities, keys (primary and foreign), relationships (named), attributes, and the appendices include a complete listing and cross referencing of the entities and attributes, which entities are used in which diagrams (in volume 2), and domains that specify the data type and suggested lengths for each attribute. The book provides clear explanations as to why the models are modeled a certain way as well as includes data examples showing the specific instances of data that could be stored in these models. The data models offered are at what I would consider a mid level of abstraction. Therefore, they offer a good level of flexibility without being overly abstract. The author will use very useful abstractions such as a "party", "product", "agreement" and "work effort" (with many specific subtypes of these entities as they apply to the various industries) but he does not go overboard by including overly generic concepts like "item" "activity", or "thing" entities. What I really like is that the author will often show multiple ways of modeling the same construct and show the pros and cons of the different ways to model a construct. Sometimes specific data modeling constructs are shown and sometimes more abstract entity models are shown. Both the volume 1 common models and volume 2 industry models have not only saved me time by being able to re-use the constructs, but they have offered some perspectives that did not occur to me and have literally been a life saver to me on many a project. I could not ask for a better reference on data modeling templates and re-usable data modeling examples!
Rating: 
Summary: Data Mart/Warehouse Companion
Review: The audience for this book is geared towards readers who would very much like to have a broad view of data models in the different industry verticals - e.g. Finance, Telcos etc Data Models are subjective and it does not hurt to look at different sources for reference. I would recommend this book to Data Warehousing consultants already familiar with the methodology and are looking for comparisons. It is not for the casual reader who would like a quick overview of Data Modeling.
Rating:
Summary: Invaluable
Review: The comprehensive industry data models and data warehouse designs in this book have been invaluable to our organization. These models are extremely well thought out and complete with Primary Keys, Foreign Keys and rational behind the data modeling choices. This book helped us deliver much higher quality solutions and saved us a tremendous amount of time. This book is worth many times its cost and we highly recommend it to any data modeler. We believe its an essential part of any data modelers toolkit.
Rating:
Summary: A Great Time Saver!
Review: The industry models defined in volume 2 have greatly accelerated our data warehouse/mart projects. We have used many of the pre-defined industry models for both internal and external projects. Again, a great time saver allowing us to "jump-start" our data projects.
Rating:
Summary: Good Comprehensive Coverage
Review: The newly revised edition of Data Model Resource Book comes in two volumes but if that's what it takes to get full coverage, I applaud the effort. I was so impressed with the health care chapter. It takes into consideration all the elements needed for accreditation by the Joint Commission. The fields are flexible and up to date. Len Silverston must have done his research well to include outcomes, a recently stressed criteria in health care data. It's nice to have a data structure to build on rather than having to start from scratch.
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