Data Modeling: Theory and Practice
by Graeme Simsion
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
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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 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.
Product Details
- ISBN-13:
- 9780977140015
- Publisher:
- Technics Publications, LLC
- Publication date:
- 06/15/2007
- Edition description:
- TECHNICS PUBLICATIONS LLC
- Pages:
- 400
- Product dimensions:
- 7.00(w) x 9.90(h) x 1.10(d)
- Age Range:
- 18 Years
Table of Contents
Introduction 1
Introduction 3
The starting point 3
Conflicting views 5
Importance of the distinction 7
Clarifying the question 11
Overview of research design 18
Organization of the book 19
Theory 23
Definitions of design and data modeling 25
Design in information systems 25
Definitions of design 27
Definitions of data modeling 30
Beliefs about the database design process 33
A model of the database design process 34
Interaction with the UoD 40
Requirements analysis 42
Conceptual data modeling 44
View integration 52
Logical data modeling 54
Physical database design 57
External schema specification 58
Process modeling 59
Beliefs from end-to-end 60
Comparison with Lawson's model 63
Lawson's characteristics of design 63
Problem 63
Process 68
Product 76
Summary and review 87
Studies of human factors in data modeling 89
The gold standard 90
Industry participation 91
Problem complexity 92
Focus of the studies 92
Generalizing the findings 93
Summary 94
What the thought-leaders think 95
Introduction 95
Design and method 96
Participants 98
Results 100
Discussion 117
Practice 121
Research design 123
Introduction 123
Research question and sub-questions 123
Research design - overview 125
Data collection and management 132
Use of statistics 136
Participants 140
Scope and stages 147
Introduction 147
Research design 148
Measures 149
The Scope and Stages questionnaire 151
Method 153
Sample 158
Results 158
Discussion and conclusions 176
How practitioners describe data modeling 183
Introduction and objectives 183
Research design 184
Method 185
Sample 187
Results 188
Discussion 194
Characteristics of data modeling 197
Introduction and objectives 197
Research design 198
Measures 198
The Characteristics of Design questionnaire 202
Method 203
Samples 205
Results 206
Analysis by property 215
Discussion and conclusions 222
Diversity in conceptual data modeling 225
Objectives and approach 225
Research design 226
Measures 227
Materials 232
Method 234
Samples 238
Results 239
Coda: The real-world solution 255
Discussion 256
Diversity in logical data modeling 265
Objectives and approach 265
Research design 267
Assessment of diversity 268
Materials 270
Method 271
Samples 274
Results 275
Discussion 292
Style in data modeling 303
Objectives and approach 303
Research design: An indicator of style 304
Measures 306
Materials 307
Method 308
Samples 310
Results 311
Discussion 320
Synthesis and conclusions 323
Synthesis and conclusions 325
Introduction 325
Answering the sub-questions 326
An alternative perspective 339
Generalizing the findings 341
Implications 343
Research directions 350
References, Appendix & Index 355
References 357
Studies of human factors in data modeling 381
Index 395
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