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The Data Model Resource CD, Vol. 1: A Library of Universal Data Models for All Enterprises, by Len Silverston
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This CD-ROM, a companion to Len Silverston's The Data Model Resource Book, Revised Edition, Volume 1, arms you with a powerful set of data models and data warehouse designs that you can use to jump-start your database development projects. It will save you countless hours and thousands of dollars in database development costs by providing the SQL code you'll need to implement the models described in the book or reverse-engineer them into your CASE tool.
You'll get actual proven models for such common business functions as ordering and managing products, handling shipments, invoicing, accounting and budgeting, managing human resources, contact management, and project management. Plus, you'll find new and expanded models for call center management, product customization, shipping and receiving, payments and collections, budgeting scenarios, and employee qualification and performance. New data mart designs are also provided in this revised edition, including financial analysis, inventory management, and shipping logistics.
You'll also want to check out The Data Model Resource Book, Revised Edition, Volume 2 (0-471-35348-5), and its companion data model sets (each sold separately), which feature universal data models tailored to various industries and applications. A free demonstration of the Volume 2 Data Models is available on this CD-ROM product.
Minimum System Requirements:
32-bit operating system such as Windows 95, Windows NT 4.0 or higher.
Hard Drive Space:
25 MB required space for installation of files.
Peripherals:
CD-ROM drive. You also will need to have the following applications to make full use of the CD-ROM: a browser such as Microsoft Internet Explorer or Netscape Navigator to open the readme.htm and navigate the demo; Visio 2000 required to view the images of the models in native format, although they can alternatively be viewed as JPEGs in a browser or another application.
- Sales Rank: #2595756 in Books
- Published on: 2001-02
- Formats: Audiobook, CD
- Original language: English
- Number of items: 1
- Dimensions: 7.60" h x .60" w x 5.40" l, .0 pounds
- Binding: CD-ROM
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
1 of 1 people found the following review helpful.
Excellent Treatment on Data Modeling for Durable Goods
By Darrell Teague
This is an excellent introductory to mid-level text on best-practices in enterprise data modeling.
Coming from a logistics/commerce consulting background, I can confirm that the recommendations are excellent.
The author clearly points out some anti-patterns that I have seen in many companies and, conversely, good models largely structured around "durable goods" businesses (selling, shipping and billing for material goods - though there are some considerations for services).
I would say this book is a "must read" for any business analyst, DBA, data-architect to prevent all-too-common errors seen in leading "CRM" and related systems that, given the acronym alone, clearly missed the boat on the concepts of sales/contact management systems.
It was only given four stars out of five as it does not really address more timely considerations of big-data, the diagrams could be more professional (and do not conform to any standard) and lastly the publisher seems to be squeezing every penny out of selling the CD and other volumes with no set discounts, etc.
0 of 0 people found the following review helpful.
Must have resource if you ever need to design a database.
By technopoetic
I've read a lot of Data Modelling books that treat the subject from a very hypothetical perspective, teaching theory, but giving no real, practical examples. This book is completely different. There's a little bit of theory, mainly exposed through explanations of real world models, but this book excels in that it contains real, working examples of data models for many different enterprise situations.
It's a wonderful resource for when you just need some pointers on how to model an invoicing module, or how to model sales orders... Extremely helpful.
3 of 3 people found the following review helpful.
Well done third volume
By Erik Gfesser
Incredibly well done follow-up to the first two volumes of Silverston's data model series (see my reviews for "The Data Model Resource Book Volume 1 (Revised Edition): A Library of Universal Data Models for All Enterprises" and "The Data Model Resource Book Volume 2 (Revised Edition): A Library of Universal Data Models by Industry Types"). As discussed in the introduction to this book, while the first volume answered the question "Where can we find a book showing a standard way to model common data model structures?" and the second volume extended the template models presented in the first volume by adding additional data model constructs that are industry specific, this third volume answers the question "How can we quickly extend and customize these models for our organization and our needs to quickly develop any data model with higher quality, even if it is specific to our enterprise?"
The patterns that Silverston and Agnew present are categorized into chapters entitled "Setting Up Roles: What Parties Do", "Using Roles: How Parties Are Involved", "Hierarchies, Aggregations, and Peer-to-Peer Relationships: The Organization of Similar Data", "Types and Categories: The Classification of Data", "Status: The States of Data", "Contact Mechanisms: How to Get in Touch", and "Business Rules: How Things Should Work". Each chapter is well laid out, similar in style to other books of this genre such as "Design Patterns: Elements of Reusable Object-Oriented Software" by Erich Gamma, Richard Helm, Ralph Johnson, and John Vlissides. In this text, each pattern is laid out in its own section that answers the following questions: "Why Do We Need This Pattern?", "How Does This Pattern Work?", "When Should This Pattern Be Used?", and "What Are the Weaknesses of the Pattern?"
In addition, an aspect of this book that this reviewer especially appreciates is a presentation of each pattern at different levels. While the data management industry habitually refers to conceptual, logical, and physical data models, because there are widely different views as to the definition and purpose behind each of these types of data models (this reviewer is all too familiar with this inconsistency from his consulting engagements), the authors devised four levels of patterns that span from the most static and the more specific (Level 1) to the most flexible and more "generalized" (Level 4). The authors explain that the two key purposes of a data model are (1) "to illustrate and communicate information requirements, and (2) "to provide a sound foundation for a database design", and because these purposes can obviously be at odds with each other, depending on the stakeholders involved, care needs to be taken during the modeling process to determine appropriateness of approach.
While this reviewer offers no suggestions for alternative terminology, the decision of the authors to use the term "generalization" to describe the transformation of very specific data model structures to those which more flexibly support data requirements is interesting (especially given their explanation that they chose to do so since the object-oriented community uses the perhaps more intuitive term "abstraction" in a different way that has a different meaning) because this reviewer is well aware that software developers also use the term when referring to an object class superset that has object class "specializations". But despite this small matter, the consistent focus of the authors on the purpose of each level of data model presented throughout the text for each group of patterns (always discussing Level 1, Level 2, and Level 3, and sometimes discussing Level 4) is highly valued by this reviewer, especially when the authors discuss these levels in relationship to the Zachman Framework and other data model classification schemes.
This reviewer also enjoyed the last two chapters, entitled "Using the Patterns" and "Socializing the Patterns", in which the authors answer the questions "How do I use, apply, and/or implement these patterns in my enterprise?", "What is an appropriate balance between requiring adherence to the patterns and allowing them to be used completely optionally and used if and when they are helpful to the modeler/designer?", "How do you get your enterprise and various people in the enterprise to adopt these patterns?", and "What types of policies or principles regarding use of the patterns would be most appropriate to get the most benefit from these patterns?"
In the first of these last two chapters (Chapter 9), the authors demonstrate how the patterns can be used to create different data models that meet different needs, using the different levels of patterns as interchangeable components and combining them to solve common data modeling challenges for circumstances surrounding the building of prototyping and scoping data models, application data models, enterprise data models, data warehouse data models, and master data management (MDM) data models. In the list of additional considerations when using generalized patterns at the end of this chapter, this reviewer appreciates their remark that "generalized structures move the change process from the typical 'data architect to DBA to developer to tester' process to a data change process, and often organizations have no formal process for data change like they have for application change" and that "this can be addressed with organizational commitment to flexible data modeling structures", especially because this reviewer experienced firsthand the impact on culture when implementing database change management processes at his last two clients.
Chapter 10 addresses getting these patterns accepted and used appropriately, discussing in detail many of the objections that one might face in the workplace as well as what the authors see as key to success in this regard: (1) understand motivations and work toward meeting them, (2) develop a clear, common, compelling vision, (3) develop trust, and (4) manage conflict effectively. In addition to understanding the motivations of others, the authors also indicate that understanding one's own motivations is also important. While this last chapter is focused on the data model patterns discussed throughout the text, in the opinion of this reviewer the psychological aspects discussed are applicable to a much broader context in the workplace, and it can only help the industry if more authors choose to address such matters. Well recommended book to all data architects and other data management professionals.
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