Developing High Quality Data Models
By- Matthew West, Director of Information Junction, UK
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.
Audience
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.
Paperback, 408 Pages
Published: December 2010
Imprint: Morgan Kaufmann
ISBN: 978-0-12-375106-5
Reviews
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"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
Contents
Preface
Chapter 1- Introduction
Chapter 2- Entity Relationship Model Basics
Chapter 3- Some types and uses of data modelsChapter 4- Data models and enterprise architecture
Chapter 5- Some observations on data models and data modelingChapter 6- Some General Principles for Conceptual, Integration and Enterprise Data Models
Chapter 7- Applying the principles for attributesChapter 8- General principles for relationships
Chapter 9- General principles for entity typesChapter 10- Motivation and overview for an ontological framework
Chapter 11- Spatio-temporal extentsChapter 12- Classes
Chapter 13- Intentionally constructed objectsChapter 14- Systems and system components
Chapter 15- Requirements specificationsChapter 16- Concluding Remarks
Chapter 17- The HQDM Framework Schema
