Data Model Patterns
| Author | : | |
| Rating | : | 4.22 (620 Votes) |
| Asin | : | 0932633749 |
| Format Type | : | paperback |
| Number of Pages | : | 568 Pages |
| Publish Date | : | 2015-08-03 |
| Language | : | English |
DESCRIPTION:
To develop a data model of an organization is to gain insights into its nature that do not come easily. Learning the basics of a modeling technique is not the same as learning how to use and apply it. Indeed, analysts are often expected to understand subtleties of an organization's structure that may have evaded people who have worked there for years.Here's help for those analysts who have learned the basics of data modeling (or "entity/relationship modeling") but who need to obtain the insights required to prepare a good model of a real business.Structures common to many types of business are analyzed in areas such as accounting, material requirements planning, process manufacturing, contracts, laboratories, and documents.TopicsIn each chapter, high-level data models are drawn from the following business areas:-The Enterprise and Its World-The Things of the Enterprise-Procedures and Activities-Contracts-Accounting-The Laboratory-Material Requirements Planning-Process Manufacturing-Documents-Lower-Level Conventions
It should be mandatory reading before starting any major data modeling or application development task. No other author has gone beyond the theoretical methodology of creating a data model to actually present and analyze real-world models that we can use every day. David Hay's book, Data Model Patterns: Conventions of Thought, is such a book. This is how I think such books should be written." --Mark Gokman, New York Power Authority . Hay does an excellent job of extracting the essence of each 'thing' in order to deal with it as more of an abstraction. Louis DAMA Newsletter"Occasionally a book comes along that can be considered a classic; that isn't tied to any particular product or version. This book is well written and well illustrated with numerous examples of the models discussed. This is a 'must buy' for your professional library." --Warren Capps, Oracle Developer"one of the practical values of your book is the set of 'ready to use' models for the most typical applications
The best I have read on the subject I have been in Data modeling for now more than 10 years and thought I knew what I was talking about. Hay proved me wrong. Even the Universal model which I was so proud to have discovered on my own is there in almost all possible uses and combination (minus one, but I'll only share it with the VERY interested ones). I have had this book at hand for almost a year now and it is one of the few I consult almost daily. My only grudge is it is based on the Oracle methodology. But this is a very personal grudge.. "Potentially valuable, but primarily as a reference." according to Christopher Wanko. I've done some data modeling, and much more process modeling, so I was familiar with Mr. Hay's objectives with respect to data and restricting the model to logical representations of data, whatever that may be.About six chapters into this book, I realize that while I could continue through to the end, I would likely find this more useful as a companion to a problem. I think the majority of non-academic readers, software practitioners if you will, will extract the necessary value from owning this book given a specific objective, i.e. I have to develop a. Jim Briggs said Data Modeling Nirvana. Tour de force! This book is up there with Gamma et al's "Design Patterns" and Booch's "Object-Oriented Design" for helping me to achieve a breakthrough understanding of--in this case--database-oriented data models. Hays walks the reader through all the important domains of business--people, assets, accounting, contracts, document management, projects--and builds a concrete data model of each domain. As he proceeds through each model he draws comparisons to the previous ones revealing patterns common to all the domains. In the last chapter he summarizes
. His work has been instrumental in identifying the fundamental structure of metadata and has helped hundreds of practitioners address issues of semantics in organization.Using the relatively simple structures hidden in apparently complex situations, Dave developed the basis for Data Model Patterns: Conventions of Thought. A subsequent work, Data Model Patterns: A Metadata Ma