- eBook ISBN 9780123751072
- Print ISBN 9780123751065
* Uses a number of common data model patterns to explain how to develop data models over a wide scope in a way that is consistent and of high quality
*Offers generic data model templates that are reusable in many applications and are fundamental for developing more specific templates
*Develops ideas for creating consistent approaches to high quality data models
This book is intended for data management professionals with job functions that include data modeler; data architect; database designer; database application developer and application architect.
"This guide to developing high quality data models provides practical instruction in understanding the core principle of data modeling and creating accurate models from complex databases. The work is divided into four sections covering the basics of data model types and uses, general principles for data model components and an ontological framework for consistent data models. A final section presents a complete, standards compliant data model created with the Jotne EPM Technology EDMVisusalExpress data modeling tool. Numerous illustrations, charts and sample programming code are included throughout the work and access to additional online content, including the sample data model, is provided. West is an experienced data modeler working in the energy field."--Book News, Reference & Research
"Overall, the book is a helpful guide for those who wish to go deep into the art of developing high quality data models. Readers will appreciate: how West connects data models with EA and business processes; the ontological approach, which offers a framework for formal, generic, and consistent models; the efficient use of diagrams for explaining the notions; and the philosophical concepts discussed throughout the text. The book is highly technical. Although it does not directly address people from academia, it will be very useful for related courses, especially those that deal with IT and business processes. Finally, the book highlights the importance of quality in data modeling for decision making."--Computing reviews.com