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This third volume of the best-selling “Data Model Resource Book” series revolutionizes the data modeling discipline by answering the question “How can you save significant time while improving the quality of any type of data modeling effort?” In contrast to the first two volumes, this new volume focuses on the fundamental, underlying patterns that affect over 50 percent of most data modeling efforts. These patterns can be used to considerably reduce modeling time and cost, to jump-start data modeling efforts, as standards and guidelines to increase data model consistency and quality, and as an objective source against which an enterprise can e

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Book ID Asin: 0470178450
Book Title: The Data Model Resource Book, Vol. 3: Universal Patterns for Data Modeling
Book Author: Len SilverstonPaul Agnew
Book Format and Price:
Book Price: unknown
Book Category: Books, Computers & Technology, Business Technology and unknown
Book Rating: 33 ratings

The Data Model Resource Book, Vol. 3: Universal Patterns for Data Modeling by Len SilverstonPaul Agnew Book Review

Name: Erik Gfesser
Rating: 5.0 out of 5 stars
Title: Welldonethirdvolume
Date: Reviewed in the United States on September 19, 2010
Review: 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.

Name: Rob Hoeting
Rating: 5.0 out of 5 stars
Title: AComprehensiveStudyofKeyDataModelPatterns
Date: Reviewed in the United States on February 19, 2009
Review: 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.

Name: C. Allen
Rating: 5.0 out of 5 stars
Title: AnEssentialResourcefortheSeriousDataModeler
Date: Reviewed in the United States on March 1, 2009
Review: “Universal Patterns for Data Modeling” is the third volume in The Model Resource Book series.In “Universal Patterns”, authors and data modeling experts Len Silverston and Paul Agnew examine the recurring patterns that are essential for architects to understand in building and maintaining enterprise data models. The book covers key patterns, including those for party, role, hierarchy, classification, status, communications, and business rules.Modeling methodology guides sometimes are overly prescriptive. However, a strength of the Silverston/Agnew book is that it recognizes that different organizations have different requirements. Each pattern is examined across four “levels.” A level represents the degree of generality or specificity with which the particular pattern is implemented. Thus, there is no underlying “one-size-fits-all” assumption, but rather a framework for thinking about the relative tradeoffs in choosing the level of generality to match given business requirements.Anyone with a serious interest in data modeling should have all three volumes on their bookshelf. However, Volumme 3, “Universal Patterns” is definitely the volume to start with if you have not already bought Volumes 1 and 2. I’ve joked with Len and Paul that Volume 3, is the “prequel.” For those who are new to this series, start with Volume 3, then go on to Vol. 1 and 2.

Name: Thomas E.
Rating: 4.0 out of 5 stars
Title: Goodbutrepeatspartsfrom1and2
Date: Reviewed in the United States on June 6, 2012
Review: The Data Model Resource Book (3) is a book about database patterns which can be used in many situations. If you are just interested in modeling something and want to check if there is a way to improve your model, but also if you just want to learn something about data modeling concepts.The chapters are always structured in a way that the patterns start of with the easiest (to understand) and also strictest way to model a problem and finish with very flexible patterns.I would say that the book is a good investment, but the first and second book already include a lot of the information that is written in the third part. That means if you don’t already have the first and second part of the series it would be better to start with them.

Name: Daniel Koger
Rating: 5.0 out of 5 stars
Title: Book3wrapsitup
Date: Reviewed in the United States on November 27, 2019
Review: Third in the series, really pulls together everything I was looking for. A real aid in my job.

Name: D. Klee
Rating: 5.0 out of 5 stars
Title: Greatdesignreference
Date: Reviewed in the United States on November 4, 2009
Review: What a great reference book! If you do anything with database design or architecture, you need to buy each book in this series. Period.

Name: Ben Bartholic
Rating: 4.0 out of 5 stars
Title: GoodBookthoughfeelsrepetitive
Date: Reviewed in the United States on April 10, 2010
Review: All in all I liked the book. The overall content of the book is good. I definitely learned new data structuring techniques that I have been able to implement at work. I did not not like how the book felt repetitive at times, I found myself skipping over a few pages in each chapter. The feel of redundancy is the reason I gave it only 4 stars.

Name: Kirill
Rating: 5.0 out of 5 stars
Title: Practicalpatternssoundadviceandgreatpeoplemanagementtips
Date: Reviewed in the United States on February 23, 2019
Review: Practical patterns, sound advice, and great people management tips all in one! Highly recommend to anyone interested in data modeling.