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The Data Model Resource Book, Vol. 1: A Library of Universal Data Models for All Enterprises, by Len Silverston
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A quick and reliable way to build proven databases for core business functions
Industry experts raved about The Data Model Resource Book when it was first published in March 1997 because it provided a simple, cost-effective way to design databases for core business functions. Len Silverston has now revised and updated the hugely successful First Edition, while adding a companion volume to take care of more specific requirements of different businesses. Each volume is accompanied by a CD-ROM, which is sold separately. Each CD-ROM provides powerful design templates discussed in the books in a ready-to-use electronic format, allowing companies and individuals to develop the databases they need at a fraction of the cost and a third of the time it would take to build them from scratch.
Updating the data models from the First Edition CD-ROM, this resource allows database developers to quickly load a core set of data models and customize them to support a wide range of business functions.
- Sales Rank: #636457 in Books
- Published on: 2001-03-06
- Original language: English
- Number of items: 1
- Dimensions: 9.25" h x 1.20" w x 7.40" l, 1.88 pounds
- Binding: Paperback
- 542 pages
Review
"I thought the models in the books were well thought out and adequately explained" (Computer Shopper February 2002)
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 compendium 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 needs 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
From the Publisher
"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 compendium 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 needs 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
Most helpful customer reviews
30 of 31 people found the following review helpful.
An important contribution to our field
By Steve Hoberman
As an analyst for a large manufacturing company's ERP implementation, I was responsible for a very complex and critical area called Classifications. Classifications was the place where all products, vendors, or customers were grouped into buckets based on similar behavior. For example, if this company manufactured vehicles, there could be classifications for hybrids, sports cars, SUVs, minivans, etc. To better understand classifications, I dived into screens, help files, and actual database tables and after several weeks, completed a classifications data model. The model I produced was very similar to the data model that appears on page 224 of "The Data Model Resource Book Volume 3: Universal Patterns for Data Modeling" by Len Silverston and Paul Agnew.
This book contains a collection of patterns, which are general building blocks that could be used as the basis for just about any type of data modeling within any industry. Classifications is one example, and there are a collection of others such as roles, statuses, and contact mechanisms. Whereas Volumes 1 and 2 in The Data Model Resource Book series contained models for common business processes or industries, this volume contains patterns that cross through all processes and industries. Consistent with the series however, the purpose of this text is to save the modeler time so instead of starting from scratch, the modeler can start from a reliable and proven foundation. Realizing these patterns exist and making them work for your particular modeling assignment can result in a higher quality data model and a greater level of consistency within your organization.
A majority of the book is dedicated to chapters which describe how to model a pattern at different levels of generalization. Level 1 is the most concrete and this is where terms and rules a business analyst are familiar with are shown, such as email address and telephone number. Level 2 through 4 go through increasingly more generized levels with Level 4 being the most generalized. The Classifications example I encountered in the ERP package for example was a Level 3 model, very generalized so that it can be leveraged by any industry. The book makes an important point that there are situations where one level is more appropriate than another, and sometimes the modeler must trade the familiarity and business rule enforcement of a Level 1 with the flexibility available in a Level 2, 3, or 4. For example, a phone number and email address from a Level 1 model would be generalized into contact mechanism data in a Level 2 model. This extra flexibility allows for accommodating other ways of contacting someone that may not have been specified (for example, via a person's "voice over IP" or Skype number). The book also makes the point that sometimes on a single model you can combine different levels for the same requirement (i.e. a hybrid approach).
Chapter 1 introduces the concept of a universal pattern as well as the terms and symbols used throughout the book. The goals for the book are also clearly articulated, in addition to the intended audience and a summary of each chapter. There is a wonderful furniture analogy used to distinguish a universal data model from a universal pattern. Universal data models (the subject of the first two volumes of The Data Model Resource Book), are similar to already constructed standard tables and chairs. The consumer can obtain this furniture instead of build the tables and chairs from scratch. Similarly, the modeler can reuse an inventory or claims universal data model instead of building it from scratch. Universal patterns are similar to the dovetail joints of the furniture, common pieces that exist in already built tables and chairs as well as custom furniture. Universal patterns are the building blocks such as the roles and statuses behind any modeling project.
Chapters 2 through 8 each focus on a particular pattern. Chapters 2 and 3 focus on parties and roles; Chapter 2 on declaration roles and Chapter 3 on contextual roles. A party is a person or organization of importance to the business, and declaration roles are those roles that are independent of any business event while contextual roles are dependent on a particular business event. For example Bob the person can have a declarative role of `Doctor', yet when an insurance claim is filed, they can also have the contextual role of `Primary Care Physician'. Chapter 4 focuses on similar structures for relating data including hierarchies, aggregations, and peer-to-peer relationships. Chapter 5 focuses on taxonomies and classifications, and Chapter 6 on patterns for states that business concepts go through. Chapter 7 contains patterns for getting in touch with parties, such as those patterns for modeling telephone number and email address. Chapter 8 focuses on how to model business rules including the rule itself, the factors involved in the rule, and the outcomes of the rule.
I was impressed with the consistency and comprehensiveness of each of these chapters. These chapters follow a similar format of demonstrating each of the four levels of detail. Each chapter begins with an explanation of the pattern and a discussion of its importance. Then for each of the four levels, there is a section on the reason for the level, how the pattern works (with lots of examples), when the pattern should be used, and the weaknesses of the pattern. I found the charts and tables to be extremely useful in the text, especially the Summary of Patterns table at the end of each chapter.
Chapter 9 focuses on how to apply these patterns in many types of efforts including both relational and dimensional modeling efforts and both application and enterprise areas of scope. As with the other chapters, there is a great summary at the end on the strengths and weaknesses of patterns with each type of effort. Chapter 10 adds the human dynamics side to incorporating patterns, as success or failure is heavily connected with people's perception or trust. Four principles are discussed, that will help acceptance and usage of the patterns: Understand motivations and work toward meeting them, Develop a clear, common, compelling vision, Develop trust, and Manage conflict effectively.
To summarize, under every data model is a set of common building blocks, clearly explained in "Universal Patterns for Data Modeling". I would recommend this book for every analyst, modeler, or architect who is striving for a level of information consistency within their organization. Whether you are just starting your modeling adventure or have been in the modeling for decades, you will find these patterns invaluable tools for every modeling effort.
0 of 4 people found the following review helpful.
Well earned 5 stars
By A Customer
The amount of work put into this book deserves more than a 5 star rating. The book covers a variety of data models and presents nearly a hundred diagrams. The author has been a consultant for database design for 20 years. This is a great work and his experience shows.
15 of 16 people found the following review helpful.
A Comprehensive Study of Key Data Model Patterns
By Robert P. Hoeting
Unlike the world of Object Oriented programming, there are very few pattern books devoted to data modeling. This is unfortunate because most business applications suffer from over-specialization & inflexibility in the data model, where change is very expensive. The few data model patterns books that do exist do not explore the depths of subject to the extent that this book does.
Based on their many years of experience, Silverston & Agnew chose to focus on the most common areas of interest (Parties, Roles, Relationships, Statuses, Classifications, Contact Mechanisms, & Rules) and offer a set of data model pattens for each. Each area has a set of "pattern levels" ranging from specific to general, listing benefits, drawbacks, & usage guidelines for each. The modeler can choose which pattern level best suites the enterprise based on perceived needs.
This book can be thought of as the "gang of four" book for data modeling. I would recommend this book for anyone engaging in any form of data modeling. You may not use the exact patterns, but it will at least serve as a catalyst for future thought.
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