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Developing High Quality Data Models
 
 

Developing High Quality Data Models, 1st Edition

 
Developing High Quality Data Models, 1st Edition,Matthew West,ISBN9780123751065
 
 
 

  

Morgan Kaufmann

9780123751065

9780123751072

408

235 X 191

The path to high quality data modeling begins with Developing High Quality Data Models.

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Key Features

* 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

Description

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.

Readership

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.

Matthew West

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

Affiliations and Expertise

Director of Information Junction, UK

Developing High Quality Data Models, 1st Edition

Preface

Chapter 1- Introduction

Chapter 2- Entity Relationship Model Basics

Chapter 3- Some types and uses of data models

Chapter 4- Data models and enterprise architecture

Chapter 5- Some observations on data models and data modeling

Chapter 6- Some General Principles for Conceptual, Integration and Enterprise Data Models

Chapter 7- Applying the principles for attributes

Chapter 8- General principles for relationships

Chapter 9- General principles for entity types

Chapter 10- Motivation and overview for an ontological framework

Chapter 11- Spatio-temporal extents

Chapter 12- Classes

Chapter 13- Intentionally constructed objects

Chapter 14- Systems and system components

Chapter 15- Requirements specifications

Chapter 16- Concluding Remarks

Chapter 17- The HQDM Framework Schema

Quotes and reviews

"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

 
 
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