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The Data Model Resource Book: A Library of Universal Data Models for All Enterprises (English Edition) 1st 版, Kindle版
"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
- ASIN : B006BBVQQY
- 出版社 : Wiley; 第1版 (2008/5/5)
- 発売日 : 2008/5/5
- 言語 : 英語
- ファイルサイズ : 14295 KB
- Text-to-Speech（テキスト読み上げ機能） : 有効
- X-Ray : 有効にされていません
- Word Wise : 有効にされていません
- 本の長さ : 542ページ
- Amazon 売れ筋ランキング: - 196,453位洋書 (の売れ筋ランキングを見る洋書)
Silverston explains in this volume that clients have inquired on numerous occasions where they can find texts showing standard ways to model data constructs, and "based on numerous experiences of using template or 'universal data models' and customizing them for various enterprises, we have concluded that usually more than 50 percent of the data model (corporate or logical) consists of common constructs that are applicable to most organizations, another 25 percent of the model is industry specific, and on average about 25 percent of the enterprise's data model is specific to that organization. Of course, as John Zachman indicates in the second volume, "Let's get pragmatic. Starting with a universal data model does not absolve anyone of the responsibility of knowing his or her own enterprise intimately, at even an excruciating level of detail! Nor does it absolve anyone from the responsibility of learning how to build data models! What you have to do is start with the universal model, and then understanding data modeling and understanding your own enterprise, make the necessary modifications to make the universal model your own."
Barker's notation is presented along with basic modeling in the introduction to this text, after which the author presents chapters on modeling people and organizations, products, ordering products, shipments, work effort, invoicing, accounting and budgeting, and human resources. Five chapters on data warehousing modeling follow, including explanations on how to create the data warehouse data model from the enterprise data model, as well as star schema designs for sales analysis, human resources, inventory management analysis, purchase order analysis, shipment analysis, work effort analysis, and financial analysis. When determining which of the three volumes you might purchase, be aware that there is some overlap between the volumes. For example, the second volume in this series contains models for products and people and organizations. In respect to these subject areas, however, the second volume in this series presents this information in respect to specific industries, while this first volume discusses them in a manner universal to all industries, significantly expanding upon any overlapping areas of the second volume while at the same time remaining industry neutral. Remember though that all of these models are to be used simply as input to your enterprise modeling efforts rather than as end states in themselves.
This reviewer recommends this text just as wholeheartedly as the second volume in this series. It can never hurt to get additional insight from other industry practitioners, and compared to other available resources the cost of this text is trivial. Note also that the second volume in this series refers to this volume in a number of different areas, so it makes sense to acquire these two volumes together.
My impression is that, given so many off-the-shelf business solutions are already available, the number of people building new data models from scratch is limited, and therefore so is the core audience of this book. Many more are faced with customizing or extending existing systems, and for them this is an interesting reference of best practices to be consulted for ideas when considering changes.