The Data Model Resource Book, Vol. 1: A Library of Universal...

Features

• Cover Type: Paperback with 542 pages
• Published by: Wiley
• Edition: 1st Edition March 6, 2001
• Written in: English
• ISBN 10 Number: 0471380237
• ISBN 13 Number: 978-0471380238
• Book Dimensions: 9 x 7.4 x 1.3 inches
• Weighs: 1.9 pounds

Product Review
"I thought the models in the books were well thought out and adequately explained" (Computer Shopper February 2002)



"I thought the models in the books were well thought out and adequately explained" -- Computer Shopper February 2002

Product Review


"The Data Model Resource Book, Revised Edition, Volume 1 is the best book I?ve seen on data architecture. It does not merely address the top levels of a data architecture (Zachman Framework row one or two); it provides both common and industry-specific logical models as well as data designs that may be customized to meet your requirements. The end result is a is a rich framework whose models span the higher and lower levels of a data architecture, including high-level models, logical models, warehouse designs, star schemas, and SQL scripts. You can use the data models, designs, and scripts as templates or starting points for your own modeling, an introduction to subject areas you might not be familiar with, a reference to validate your existing models, and a help to building an enterprise data architecture. The book provides techniques to transform models from one level to another, as well as tips and techniques for getting the appropriate levels of abstraction in the models. Instance tables (sample data) help bring the models to life. I have customized and used the models from the first edition on many projects in the last two years?it is an invaluable resource to me."
--Van Scott, President, Sonata Consulting, Inc.

"Len Silverston has produced an enormously useful two-volume enyclopedia of generic (but not too generic) data models for an extensive set of typical enterprise subject areas, and for various industries that any data modeler will likely encounter at some point in his or her career. The material is clearly written, well organized, and goes below the obvious to some of the more perverse and difficult information requirements in an enterprise. This is an invaluable resource for doing one's homework before diving into any modeling session; if you can't find it here, there is certainly a very similar template that you can use for just about any situation with which you might be faced."
--William G. Smith, President, William G. Smith & Associates

"In today's fast-paced e-oriented world, it is no longer acceptable to bury business constraints in hard-to-change data structures. Data architects must comprehend complex requirements and recast them into data architecture with vision for unforeseen futures. Len's models provide an outstanding starting point for novice and advanced data architects for delivering flexible data models. These models position an organization for the business rule age. Their proper implementation and customization allows the organization to externalize and manage business policies and rules so that the business can proactively change itself. In this way, the data architecture, based on Len's models and procedures for customizing them, becomes by design the foundation for business change."
--Barbara von Halle, Founder, Knowledge Partners, Inc., Co-author of Handbook of Relational Database Design

"These books are long overdue and a must for any company implementing universal data models. They contain practical insights and templates for implementing universal data models and can help all enterprises regardless of their level of experience. Most books address the requirements for data models but give little in the way of practical advice. These books fill in that void and should be utilized by all enterprises."
--Ron Powell, Publisher, DM Review

"Businesses across the world are demanding quality systems that are built faster by IT shops. This book provides a foundation of patterns for data modelers to expand upon and can cut days, if not weeks, off a project schedule. I have found The Data Model Resource Book, Revised Edition, Volume 1 valuable as a resource for my modeling efforts at L.L. Bean, Inc. and feel it is an essential component in any modelers toolkit."
--Susan T. Oliver, Enterprise Data Architect, L.L. Bean, Inc.

"I was first introduced to The Data Model Resource Book three years ago when I was hired by a firm who wanted an enterprise data model. This company did not believe the dictum that ?all companies are basically the same;? they felt they were somehow unique. After a little analysis with Len Silverston's help, we found that we were actually quite a bit the same: we had customers, accounts, employees, benefits, and all the things you'd find in any corporation. All we had to do was adapt the product component of Len's book and we were ready to move ahead with a great framework for all of our data. A CD-ROM that accompanies the book provided scripts to build the model in Oracle very quickly. We then began mapping all of our detailed data types to the enterprise model and, voila, we could find a place for all of those various spellings and misspellings of Account Number.
Volume 2 of this revised edition provided even more exciting features: models of industry-specific data. I began to see interesting patterns that permeated this volume. For example, a reservation is a reservation, whether you're an airline, a restaurant, or a hotel. (We even have something similar in the oil industry--the allocation.)
Another concept from the book that has changed my thinking and vocabulary is the word "party." I recently managed a project in which an employee could also function as a customer and as an on-line computer user. The team was in disagreement regarding a name for this entity; but after checking The Data Model Resource Book, we realized that here we had a party playing three roles.
Whether your job is to jump-start a data warehouse project or borrow ideas for any subject area in your next operational database, I highly recommend The Data Model Resource Books, Revised Edition, Volumes 1 and 2 as your bible for design."
--Ted Kowalski, Equilon Enterprises LLC, Author of Opening Doors: A Facilitator's Handbook

Reader Reviews
I couldn't possibly review the entire content of the work in the space provided. What I can do is give you an overview of the contents and tell you what I like about this work and what I find as weaknesses. A more detailed review is available on my website due to review size constraints here. Volume I contains universal models for: - People and Organizations - Products - Ordering Products - Shipments - Work Effort - Invoicing - Accounting and Budgeting - Human Resources There is a short section on how to transform these logical data models into data warehouse models, along with some sample star schema models for Sales Analysis and Human Resources at the detailed level, with some brief examples of other star schema for the other models in the first half of the book. This title also includes about forty pages on how to use and implement universal data models in general. While this attempts to cover at a high level the basic activities of data and process modelling along with database design, the reader should understand that the author could not possibly cover the section in any significant detail in the same book. Other texts I've recommended on this website would fill those needs. Strengths The first really joy of this work is that Silverston indicates at the beginning that he expects that these models will be revised, customized, and enhanced when applied to a real life problem. This obvious approach demonstrates Silverston's wealth of industry experience, over twenty years of information technology work. As I worked my way through the models, it became obvious that these were based on data modelling efforts in the real world. The models themselves show a maturity that is rarely found in many data modelling works. There are still complexities that are not addressed, but I wouldn't be looking for those sorts of details in this type of book. I find the inclusion of sample data values for key entities a great strength of this work. Overall the models themselves follow, for the most part, good data modelling style and standards. The logical models are normalized, but in a practical way, not in an academic definition of normalized. What I mean by that is there are a handful of attributes that would not meet the strict criteria of normalization, but they have been denormalized in a way that is very, very common. For instance, one can find Address Line One and Address Line Two attributes in the Person and Organizations model. I don't consider this a weakness, but the author should have indicated that short cut was being used in this case. The fact that this work includes a Party concept (and did even in its first edition) is admirable. Silverston's enhancements to the Party models since his first work show how flexible and valuable this concept can be. In the last year or so, the pendulum has swung the other way; now people can be quite irritated if a modeller does not understand the Party concept. He even includes 3 common design options for implementing Party. Weaknesses The book uses the Oracle/Barker notation for its diagrams and sample models. While the use of this notation is common due to the fact that Oracle modelling tools have a large installation base, its always seems odd to me that several data modelling books that hope to discuss vendor-independent and tool independent approaches to a logical data model choose to use a notation that is exclusive to one tool on the market. I don't believe there's anything wrong with the notation; I find it clear and acceptable for data modelling. I just wish that authors would choose a more commonly understood notation. A brief explanation of the notation is included in the first chapter of this work. A common drawback of many Oracle models I see is that they follow a naming standard for relationships that leaves out the implied `to be' form of the verb in the relationship name. So instead of using "is included in" the relationship, the sample modes might use "included in". That in itself is not really a problem. The problem becomes apparent when modellers tend to use relationship names that look or act more like nouns than verbs. For instance, in the Invoice Specific Roles model, there's a relationship between SALES INVOICE and INTERNAL ORGANIZATION. This relationship is labelled "billed from" on one side "the sender of" on the other. These do not, to me, appear to be the same relationship, even if they are on the model. This sort of discrepancy can lead to modelling errors and oversights. The full verb-based approach to naming relationships would most likely use labels such as "sends" and "is sent by", clearly the same relationship. There are also several relationships that use the label "of" or "for", which to me add no more of a definition to the relationship than existence of a line between the two entities. These are not isolated occurrences; they appear to be a style of modelling used throughout the book. Silverston's data modelling style is more informal than mine in that he does follow many common standard approaches to creating and naming modelling objects, but deviates from them in several places. He does follow, for the most part, a QUALIFIER NOUN CLASSWORD approach to naming attributes. This brings up another weakness in this work, something that I'd hope would be changed in the next edition: these models are very tailored to American businesses. The use of the name above "Total Dollars Allowed" is not acceptable to me, even when used in a U.S. business. These weaknesses are not significant, nor do they impact greatly on my decision to recommend this book. I'd hope that future editions would improve upon the weakness, but they are obstacles to using the models in the real world. Please see my other review on this site concerning this included CD.