Data Modeling Theory and Practice

Theory & Practice

By: Graeme Simsion

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Paperback | 1 September 2009

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416 Pages

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Graeme Simsion, author of several bestsellers including The Rosie Project, provides a detailed review of the extensive literature on data modeling and logical database design, referencing nearly 500 publications, with a strong focus on their relevance to practice.

DATA MODELING THEORY AND PRACTICE is for practitioners and academics who have learned the conventions and rules of data modeling and are looking for a deeper understanding of the discipline. The coverage of theory includes a detailed review of the extensive literature on data modeling and logical database design, referencing nearly 500 publications, with a strong focus on their relevance to practice. The practice component incorporates the largest-ever study of data modeling practitioners, involving over 450 participants in interviews, surveys and data modeling tasks. The results challenge many longstanding held assumptions about data modeling and will be of interest to academics and practitioners alike.

Graeme Simsion brings to the book the practical perspective and intellectual clarity that have made his Data Modeling Essentials a classic in the field. He begins with a question about the nature of data modeling (design or description), and uses it to illuminate such issues as the definition of data modeling, its philosophical underpinnings, inputs and deliverables, the necessary behaviors and skills, the role of creativity, product diversity, quality measures, personal styles, and the differences between experts and novices.

Data Modeling Theory and Practice is essential reading for anyone involved in data modeling practice, research, or teaching.

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Non-Fiction Computing & I.T.Computer Science Reference, Information & Interdisciplinary Subjects Research & Information Data Analysis Graphical & Digital Media Applications 3D Graphics & Modelling Business & Management Databases

Introduction	p. 1
Introduction	p. 3
The starting point	p. 3
Conflicting views	p. 5
Importance of the distinction	p. 7
Clarifying the question	p. 11
Overview of research design	p. 18
Organization of the book	p. 19
Theory	p. 23
Definitions of design and data modeling	p. 25
Design in information systems	p. 25
Definitions of design	p. 27
Definitions of data modeling	p. 30
Beliefs about the database design process	p. 33
A model of the database design process	p. 34
Interaction with the UoD	p. 40
Requirements analysis	p. 42
Conceptual data modeling	p. 44
View integration	p. 52
Logical data modeling	p. 54
Physical database design	p. 57
External schema specification	p. 58
Process modeling	p. 59
Beliefs from end-to-end	p. 60
Comparison with Lawson's model	p. 63
Lawson's characteristics of design	p. 63
Problem	p. 63
Process	p. 68
Product	p. 76
Summary and review	p. 87
Studies of human factors in data modeling	p. 89
The gold standard	p. 90
Industry participation	p. 91
Problem complexity	p. 92
Focus of the studies	p. 92
Generalizing the findings	p. 93
Summary	p. 94
What the thought-leaders think	p. 95
Introduction	p. 95
Design and method	p. 96
Participants	p. 98
Results	p. 100
Discussion	p. 117
Practice	p. 121
Research design	p. 123
Introduction	p. 123
Research question and sub-questions	p. 123
Research design - overview	p. 125
Data collection and management	p. 132
Use of statistics	p. 136
Participants	p. 140
Scope and stages	p. 147
Introduction	p. 147
Research design	p. 148
Measures	p. 149
The Scope and Stages questionnaire	p. 151
Method	p. 153
Sample	p. 158
Results	p. 158
Discussion and conclusions	p. 176
How practitioners describe data modeling	p. 183
Introduction and objectives	p. 183
Research design	p. 184
Method	p. 185
Sample	p. 187
Results	p. 188
Discussion	p. 194
Characteristics of data modeling	p. 197
Introduction and objectives	p. 197
Research design	p. 198
Measures	p. 198
The Characteristics of Design questionnaire	p. 202
Method	p. 203
Samples	p. 205
Results	p. 206
Analysis by property	p. 215
Discussion and conclusions	p. 222
Diversity in conceptual data modeling	p. 225
Objectives and approach	p. 225
Research design	p. 226
Measures	p. 227
Materials	p. 232
Method	p. 234
Samples	p. 238
Results	p. 239
Coda: The real-world solution	p. 255
Discussion	p. 256
Diversity in logical data modeling	p. 265
Objectives and approach	p. 265
Research design	p. 267
Assessment of diversity	p. 268
Materials	p. 270
Method	p. 271
Samples	p. 274
Results	p. 275
Discussion	p. 292
Style in data modeling	p. 303
Objectives and approach	p. 303
Research design: An indicator of style	p. 304
Measures	p. 306
Materials	p. 307
Method	p. 308
Samples	p. 310
Results	p. 311
Discussion	p. 320
Synthesis and conclusions	p. 323
Synthesis and conclusions	p. 325
Introduction	p. 325
Answering the sub-questions	p. 326
An alternative perspective	p. 339
Generalizing the findings	p. 341
Implications	p. 343
Research directions	p. 350
References, Appendix & Index	p. 355
References	p. 357
Studies of human factors in data modeling	p. 381
Index	p. 395
Table of Contents provided by Ingram. All Rights Reserved.

Data Modeling Theory and Practice

Theory & Practice

At a Glance

Paperback

Shipping

How to return your order

Defective items

You Can Find This Book In

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