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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

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.

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 Part 1 Motivations and Notations Chapter 1 Introduction 1.1 Some Questions about Data Models 1.2 Purpose 1.3 Target Audience 1.4 What Is a Data Model? 1.5 Why Do We Do Data Models? 1.6 Approach to Data Modeling 1.7 Structure of This Book Chapter 2 Entity Relationship Model Basics 2.1 Oh, Its Boxes and Lines Again 2.2 Graphical or Lexical 2.3 Graphical Notations: Complexity vs. Understandability vs. Capability 2.4 Language and Notation Elements 2.5 Express-G 2.6 Notation for Instances and Classes 2.7 Layout of Data Models 2.8 Reflections Chapter 3 Some Types and Uses of Data Models 3.1 Different Types of Data Models 3.2 Integration of Data and Data Models 3.3 Concluding Remarks Chapter 4 Data Models and Enterprise Architecture 4.1 The Business Process Model 4.2 Information Architecture 4.3 Information Operations 4.4 Organization 4.5 Methodologies and Standards 4.6 Management 4.7 Wider Infrastructure 4.8 Enterprise Architecture Mappings 4.9 The Process/Data Balance Chapter 5 Some Observations on Data Models and Data Modeling 5.1 Limitations of Data Models 5.2 Challenges in Data Modeling Part 2 General Principles for Data Models Chapter 6 Some General Principles for Conceptual, Integration, and Enterprise Data Models 6.1 Data Modeling Approach 6.2 General Principles 6.3 Understanding Relationships 6.4 Principles for Data Models 6.5 Naughtiness Index Chapter 7 Applying the Principles for Attributes 7.1 Looking for Attributes Representing Relationships 7.2 Identifiers 7.3 What Other Attributes Might You Expect? 7.4 Concluding Remarks on Attributes Chapter 8 General Principles for Relationships 8.1 Example of Inappropriate Cardinalities-Batch and Product Type 8.2 Example of Inappropriate Cardinalities-Packed Products 8.3 An Example of Inappropriate Cardinalities-Ship 8.4 A Good Example of Applying the Principles for Relationships-Transfer and Storage 8.5 Concluding Remarks Chapter 9 General Principles for Entity Types 9.1 An Example-Combined Entity Types 9.2 An Example-Stock 9.3 Getting Subtypes Wrong 9.4 An Example of Fixed Hierarchies-Stock Classification 9.5 Getting the Right Level of Abstraction 9.6 Impact of Using the Principles Part 3 An Ontological Framework for Consistent Data Models Chapter 10 Motivation and Overview for an Ontological Framework 10.1 Motivation 10.2 Ontological Foundation 10.3 A Data Model for the Ontological Foundations 10.4 Closing Remarks Chapter 11 Spatio-Temporal Extents 11.1 Parts 11.2 Individuals and States 11.3 Inheritance of Properties by Substates 11.4 Space and Time 11.5 Ordinary Physical Objects 11.6 Levels of Reality 11.7 Activities and Events 11.8 Associations 11.9 A Data Model for Individuals Chapter 12 Classes 12.1 What Is a Set? 12.2 Sets and Four-Dimensionalism 12.3 Some Different Kinds of Set Theory 12.4 A High Level Data Model for Classes 12.5 Properties and Quantities 12.6 Scales and Units 12.7 Kinds 12.8 Concluding Remarks Chapter 13 Intentionally Constructed Objects 13.1 Introduction 13.2 Functional Objects 13.3 Socially Constructed Objects 13.4 Ownership 13.5 Agreements 13.6 Contracts 13.7 Organizations 13.8 Product 13.9 Representation 13.10 Concluding Remarks Chapter 14 Systems and System Components 14.1 What Are Systems and System Components? 14.2 The Nature of System Components 14.3 Another Example: A Football Match 14.4 Similarities, Differences, and Relationships to Other Things 14.5 Do I Need a Separate Set of Classes for System Components? 14.6 Extending the Framework for System and System Component 14.7 Concluding Remarks Chapter 15 Requirements Specification 15.1 A Process for Procurement 15.2 Requirements Specification Chapter 16 Concluding Remarks Part 4 The HQDM Framework Schema Chapter 17 HQDM_Framework 17.1 Thing and Abstract Object 17.2 Class and Class of Class 17.3 Relationship and Class of Relationship 17.4 Spatio-Temporal Extent and Class of Spatio-Temporal Extent 17.5 Event, Class of Event, and Point in Time 17.6 State and Individual 17.7 Physical Object 17.8 Ordinary Physical Object 17.9 Kind of Individual and Subtypes 17.10 Kind of System and System Component 17.11 Period of Time and Possible Worlds 17.12 Physical Properties and Physical Quantities 17.13 Association 17.14 Activity 17.15 Participant 17.16 Role, Class of Activity, and Class of Association 17.17 System 17.18 System Component 17.19 Installed Object 17.20 Biological Object 17.21 Ordinary Biological Object 17.22 Biological System 17.23 Person 17.24 Biological System Component 17.25 Intentionally Constructed Object 17.26 Functional Object 17.27 Ordinary Functional Object 17.28 Functional System 17.29 Socially Constructed Object 17.30 Party 17.31 Organization and Language Community 17.32 Employment 17.33 Organization Component and Position 17.34 Money 17.35 Ownership 17.36 Transfer of Ownership 17.37 Socially Constructed Activity 17.38 Class of Socially Constructed Activity 17.39 Agreement 17.40 Contract 17.41 Offer and Acceptance of Offer 17.42 Sale of Goods 17.43 Sales Product, Product Brand, and Sales Product Version 17.44 Offering 17.45 Sign and Pattern 17.46 Requirement and Requirement Specification Appendix: A Mapping between the HQDM Schema and ISO 15926-2 Index

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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