- Taschenbuch: 532 Seiten
- Verlag: Technics Publications, LLC (2. Februar 2011)
- Sprache: Englisch
- ISBN-10: 1935504053
- ISBN-13: 978-1935504054
- Größe und/oder Gewicht: 17,8 x 3 x 25,4 cm
- Durchschnittliche Kundenbewertung: 1 Kundenrezension
- Amazon Bestseller-Rang: Nr. 246.931 in Fremdsprachige Bücher (Siehe Top 100 in Fremdsprachige Bücher)
Enterprise Model Patterns: Describing the World (UML Version) (Englisch)
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Über den Autor und weitere Mitwirkende
Since the early 1980s, David Hay has been a pioneer in the use of process and data models to support strategic planning, requirements analysis, and system design. He has developed enterprise models for many industries, including, among others, pharmaceutical research, oil refining and production, film and television, and nuclear energy. In each case, he found the relatively simple structures hidden in formidably complex situations. Mr. Hay has published several books and numerous articles. He is a frequent speaker at professional society conferences.
David Hay führt einen schrittweise in die Komplexität der Probleme der realen welt ein, ohne sich vor Schwierigkeiten zu drücken.
Es wird glücklicherweise auf Modellierungstheorie verzichtet und viele konzeptuelle Ideen wie Metamodellierung werden anhand konkreter, brauchbarer Nicht-Schul-Beispielen erläutert.
Es können problemlos einzelne Kapitel individuell gelesen werden, die zusätzlich benötigten Seiten werden schnell gefunden.
Es spricht sowohl Modellierungs-Experten an, welche ihre Erfahrungen mit den gegebenen Beispielen überprüfen und überdenken können, aber auch für Anfänger oder Fortgeschrittene birgt diese Buch ein grosser Fundus an Wissen und Erfahrung.
Auch für Besitzer seines Vorgängerwekes "Data Model Patterns" ist dieses Buch 100% zu empfehlen.
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The author starts the book out with an explanation as to why a new way of data modeling (using his UML syntax) is needed. He then covers the conventions of his DSL (by the way, he does not refer to is as a DSL... that is just how I classified it in my own mind) which is a constrained UML language consisting of only class diagrams.
Using only class diagrams bothered me at first too. How do you show state, communication, timing, deployment, etc.? Well it turns out that one of the constraints of the DSL is to limit activities to the data in an activity, not the activities themselves. He leaves that to the other diagrams, that are not part of his modeling goals.
I became more and more comfortable with the constraints as I read on. I think the author made the right choice in limiting the DSL the way he did. He goes through 4 levels of abstraction in his process. If he had not out boundaries in place, it would have been way too big in scope to be usable.
The author the then continues on with several chapters that take you through all 4 levels (Level 0, 1, 2, and 3) of abstraction used in the author's modeling process.
Level 0: An abstract template that underlies level 1
Level 1: A model of an enterprise in general. Includes chapters on People and Organization, Geographic Locations, Assets, Activities, and Timing.
Level 2: A more detailed model describing specific functional areas. Includes chapters on Facilities, Human Resources, Communications and Marketing, Contracts, Manufacturing, and The Laboratory.
Level 3: A model of a specific industry. Includes chapters on Criminal Justice, Microbiology, Banking, Oil Field Production, and Highway Maintenance.
Each chapter contains tons of diagrams.
This book is an excellent guide to abstraction as well as business modeling. Following the author through the different levels of models will greatly increase your analysis skills and modeling skills.
If you are a business analyst, DBA, or software architect this book is mandatory reading.
The author explains how data modeling can be applied to understanding an organization and its functions. He uses the Zachman Framework which explains multiple perspectives on systems development: planner, owner, architect, designer, builder and functioning system user. Be ready to think like an architect who is modeling the business rather than as a database designer who is concerned with designing tables and columns.
David Hay has organized data models into multiple levels and explains the purpose and structure of each level. Upon reflection, I see that these levels correspond to the levels in the TOGAF Enterprise Continuum. The data models in the book are rendered using Unified Modeling Language (UML). This was a good choice in understanding data modeling and data architecture.
The last part of the book focuses on applying data models to specific industries: criminal justice, microbiology, banking, oil field production and highway maintenance. These topics are thought provoking and can be extended to other industries. For example, I can see parallels between banking industry and the insurance industry data models.
I give this book very high marks and find it thought provoking - it is what I would expect in a great book about data modeling. The topics are very current. The information resource model is helpful in understanding Big Data and the activity model is useful in understanding business process management and workflow. Thumbs up for Enterprise Model Patterns: Describing the World by David Hay.
Also various aspects of metamodelling or template modelling as David Hay is naming it gives you very good tools into your rucksack of thoughts.
I'm not a native english speaking person but nevertheless the examples and concepts are very illustralively written and shown, so that it's a pleasure to read.
It's no problem at all to pick a chapter in the middle of the book; very quickly you'll find the pages necessary to read in advance.
Alltogether a very usefull book for modelling experts to proove their thoughts and ideas and find new ones, but also for intermediates or even beginners.
David Hay is not boring you with modelling theory but pragmatically brings you further with many real-world examples, and nevertheless he is very precise and consistent with notifications and his patterns.
Even, when you own his previous book "Data Model Patterns", go for It! it's worth every buck.
The fact that this book uses UML is a big leap forward in that it shows you that UML can be effectively used for data modeling. It also gives you the opportunity to claim understanding of this language. The book also refines many of the concepts in the original data model patterns. While I have finished it, I have only scratched the surface. I need to go back and really study some of the models - not so that I know that particular industry or set of information (although that is a great opportunity) - but so that I can solidify my understanding of finding the universal patterns evident in any information set or problem I am presented with.
Finally, Dave shows that data modeling really is a window to an essential understanding of any information set. When you begin to really get into the patterns Dave presents you see how that you as a data modeler can really begin to understand the business (if you are modeling a business) better than the business people do! The reason is so few people focus on understanding the essential nature of things apart from how they are implemented. It was a true pleasure to read this book from a giant in the field of data modeling who really does. And I'm even getting used to reading these "up and to the left" models which is really saying something!
When I first looked though, I thought, as many with long experienced might, was "well, I know all this, and have done even better models of many of these things, so what's new?". Over time, I realized that what is **new** is putting it all together, and including so many insights and observations from David Hay's deep experience, that begins to represent a foundation for a serious and deep profession.
Yet in practice, in most standard software engineering environments, UML versus an E/R modelling language, has been a huge, meaningless non-issue that puts up artificial barriers to success. This work begins to break down that roadblock, and help make clear that the language in which a model is created is a mostly separate matter from what is modeled. Especially in a day when their are tools that map between these languages, and between these and OWL, for example.
More broadly, I find that there is so much overlap and lack of coordination, between so many things in computer science and engineering, from metadata management to enterprise architecture to ontology, to model driven development, with so much tunnel vision, even among these interests that *all" profess to be looking at "the big picture," that it is hard for me to get people in any of these other fields to take into account what David Hay done here, which is a start at pulling together some of the threads.
In fact, my only complaint is that this profession is called in the book, and by other reviewers "data modelling", even though the title is Enterprise Model Patterns. This makes it seem somewhat more retrospective than it is. I complain about this because:
1. Most people identify *data* modelling with what is in a database. But the same information, with the same relationships, must appear in user interfaces, messages, process specifications, component contracts, web data relationships, and as parts of shared industry ontologies. This book could help all of these endeavors, and help productivity if the people engaged in them were able to separate the important ideas from the technological environment. In no other engineering field is there so much decade over decade reinventions, as technology changes.
2. David Hay defines an enterprise data model to be "An E/R Model whose domain is an entire business or government agency". But entire domains of human endeavor, such as money transfer, organic chemistry, the practice of information modelling itself, securities clearance, need these kinds of models, and in today's interconnected world, they are sorely needed. So, to me, it is somewhat narrow to see the focus on single businesses. (Especially as the book itself shows that there are patterns that apply to entire domains of human endeavor.
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