Developing High Quality Data Models - Softcover

West, Matthew

Softcover

ISBN 10: 0123751063 ISBN 13: 9780123751065

Publisher: Morgan Kaufmann, 2011

Synopsis

Developing High Quality Data Models provides an introduction to the key principles of data modeling. It explains the purpose of data models in both developing an Enterprise Architecture and in supporting Information Quality; common problems in data model development; and how to develop high quality data models, in particular conceptual, integration, and enterprise data models.

The book is organized into four parts. Part 1 provides an overview of data models and data modeling including the basics of data model notation; types and uses of data models; and the place of data models in enterprise architecture. Part 2 introduces some general principles for data models, including principles for developing ontologically based data models; and applications of the principles for attributes, relationship types, and entity types. Part 3 presents an ontological framework for developing consistent data models. Part 4 provides the full data model that has been in development throughout the book. The model was created using Jotne EPM Technologys EDMVisualExpress data modeling tool.

This book was designed for all types of modelers: from those who understand data modeling basics but are just starting to learn about data modeling in practice, through to experienced data modelers seeking to expand their knowledge and skills and solve some of the more challenging problems of data modeling.

• 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

About this title

About the Author

Matthew West spent over 20 years as a leading data modeler for Shell where he was a key technical contributor to data modeling and data management standards and their application. Matthew was responsible for Shell's Downstream Data Model. He currently serves as the Director of Information Junction, a data architecture and analysis consultancy in the UK. He is also a key contributor to ISO 15926 (Lifecycle integration of process data) and ISO 8000 (Data and Information Quality). Matthew is a Visiting Professor at the University of Leeds

From the Back Cover

A multitude of problems is likely to arise when developing data models. With dozens of attributes and millions of rows, data modelers are always in danger of inconsistency and inaccuracy. The development of the data model itself could result in difficulties presenting accurate data. The need to improve data models begins with getting it right in the first place.

Using real-world examples, Developing High Quality Data Models walks the reader through identifying a number of data modeling principles and analysis techniques that enable the development of data models that both meet business requirements and have a consistent basis. The reader is presented with a variety of generic data model patterns that both exemplify the principles and techniques discussed and build upon one another to give a powerful and integrated generic data model. This model has wide applicability across many disciplines in government and industry, including but not limited to energy exploration, healthcare, telecommunications, transportation, military defense, transportation, and more.

Edition details

• Publisher: Morgan Kaufmann
• Publication date: 2011
• Language: English
• ISBN 10: 0123751063
• ISBN 13: 9780123751065
• Binding: Paperback
• Edition number: 1
• Number of pages: 408