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Modelling Business Information

Modelling Business Information

Keith Gordon

(2017)

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Book Details

Abstract

It is almost universally accepted that requirements documents for new or enhanced IT systems by business analysts should include a ‘data model’ to represent the information that has to be handled by the system. Starting from first principles, this book will help business analysts to develop the skills required to construct data models through comprehensive coverage of entity relationship and class modelling, in line with, and beyond, the BCS Data Analysis syllabus.
It is almost universally accepted that requirements documents for new or enhanced IT systems by business analysts should include a ‘data model’ to represent the information that has to be handled by the system. Starting from first principles, this book will help business analysts to develop the skills required to construct data models through comprehensive coverage of entity relationship and class modelling, in line with the BCS Data Analysis syllabus. In addition to covering the topics in the syllabus, the book also includes extra information of interest including data model quality and taking a requirement model into database design.
‘Anyone interested in a thoughtful, well-done text on how to do high-quality business analytical data modelling should definitely proceed with this book.’
David Hay
'As the roles of Data and Business Analysts become more intertwined, this book is timely in its publication. Businesses often fail to recognise information is a key resource and are confused by how it is presented or overwhelmed its complexity during use. Keith brings to the forefront of the readers mind the importance of communicating and analysing the relationship between Business, Information, Systems and Data, and the value in developing models cooperatively, gaining "consensus, not perfection“ from stakeholders. Simple everyday examples and analogies to support the readers understanding and make the subject more relatable are used. I enjoyed reading the book and completing the exercises. An excellent learning aid for Analysts who are new to modelling or need reminding of good practice.'
Katie Walsh
'Keith Gordon’s wonderfully compact yet thorough introduction to business-friendly information modelling is a terrific contribution to the field. Globally, there’s a surge of interest in data modelling as a powerful tool for improving communication, especially with professionals who used to think business-oriented entity-relationship modelling didn't need to be in their tool kits. Business analysts, Agile developers, data scientists, big data specialists, and other professionals will all benefit from Keith’s work.'
Alec Sharp
'“Modelling Business Information” provides an introduction to data modeling, to the nomenclature used by common modeling techniques, and to techniques for representing common patterns. This is a useful book for business analysts who are creating the information model as well as for business and IT users who need to understand a data model.'
Keith W. Hare
Keith Gordon is an independent consultant and lecturer specialising in data management and business analysis. He has spent over 50 years in technical, education and training environments as an engineer, computer consultant, data manager, business analyst, education and training manager.

Table of Contents

Section Title Page Action Price
Cover Cover
Copyright Page vi
CONTENTS vii
LIST OF FIGURES AND TABLES x
ABOUT THE AUTHOR xiii
FOREWORD xv
ACKNOWLEDGEMENTS xviii
GLOSSARY xix
INTRODUCTION xxv
PART 1: THE BASICS 1
1 WHY BUSINESS ANALYSTS SHOULD MODEL INFORMATION 3
WHAT IS BUSINESS ANALYSIS? 3
INFORMATION AND DATA 5
THE IMPORTANCE FOR A BUSINESS ANALYST OF UNDERSTANDING INFORMATION NEEDS 6
THE ROLE OF MODELS IN BUSINESS ANALYSIS 7
DATA MODELS AND DATA 10
ENTITY RELATIONSHIP MODELLING 11
CLASS MODELLING 12
USE OF DATA MODELS IN BUSINESS ANALYSIS 13
WHAT MAKES A GOOD DATA MODEL? 14
INTRODUCING DATA ANALYSIS 14
2 MODELLING THE THINGS OF INTEREST TO THE BUSINESS AND THE RELATIONSHIPS BETWEEN THEM 16
ENTITIES AND OBJECTS 16
NAMING OF ENTITY TYPES AND OBJECT CLASSES 18
INTRODUCTION TO RELATIONSHIPS AND ASSOCIATIONS 19
RELATIONSHIP NOTATION IN ENTITY RELATIONSHIP MODELS 20
ASSOCIATION NOTATION IN UML CLASS MODELS 22
DEGREES OF CARDINALITY AND OPTIONALITY 24
MULTIPLE RELATIONSHIPS AND ASSOCIATIONS 27
RECURSIVE RELATIONSHIPS AND REFLEXIVE ASSOCIATIONS 29
EXERCISES FOR CHAPTER 2 30
3 MODELLING MORE COMPLEX RELATIONSHIPS 32
THE PROBLEMS WITH MANY-TO-MANY RELATIONSHIPS AND ASSOCIATIONS 32
RESOLVING ENTITY RELATIONSHIP MODEL MANY-TO-MANY RELATIONSHIPS 33
RESOLVING CLASS MODEL MANY-TO-MANY ASSOCIATIONS 35
THE ‘BILL OF MATERIALS’ STRUCTURE 36
MUTUALLY EXCLUSIVE RELATIONSHIPS AND ASSOCIATIONS 39
GENERALISATION AND SPECIALISATION IN ENTITY RELATIONSHIP MODELS 41
GENERALISATION AND SPECIALISATION IN CLASS MODELS 43
AGGREGATION AND COMPOSITION 46
EXERCISES FOR CHAPTER 3 48
4 DRAWING AND VALIDATING INFORMATION MODEL DIAGRAMS 50
THE MODEL DRAWING PROCESS 50
IDENTIFYING THE ENTITY TYPES OR THE OBJECT CLASSES 51
IDENTIFYING THE RELATIONSHIPS OR ASSOCIATIONS 53
DRAWING THE INITIAL DIAGRAM 54
VALIDATING THE DIAGRAM 56
EXERCISES FOR CHAPTER 4 63
5 RECORDING INFORMATION ABOUT THINGS 65
REVISITING ENTITY TYPES, OBJECT CLASSES, RELATIONSHIPS AND ASSOCIATIONS 65
INTRODUCTION TO ATTRIBUTES 66
THE NAMING OF ATTRIBUTES 69
ENTITY TYPE, OBJECT CLASS OR ATTRIBUTE? 69
UNIQUE IDENTIFIERS 72
DOMAINS 74
THE UML EXTENDED ATTRIBUTE NOTATION 75
SHOWING OPERATIONS ON CLASS MODELS 77
EXERCISES FOR CHAPTER 5 79
6 RATIONALISING DATA USING NORMALISATION 81
WHAT IS NORMALISATION? 81
THE RELATIONAL MODEL OF DATA 82
THE RULES OF NORMALISATION 84
STARTING THE NORMALISATION PROCESS 85
FIRST NORMAL FORM 86
SECOND NORMAL FORM 89
THIRD NORMAL FORM 90
THE THIRD NORMAL FORM DATA MODEL 94
CANDIDATE KEYS, PRIMARY KEYS AND ALTERNATE KEYS 95
THE RELATIONSHIP OF NORMALISATION TO MODELLING 95
EXERCISES FOR CHAPTER 6 96
PART 2: SUPPLEMENTARY MATERIAL 97
7 OTHER MODELLING NOTATIONS 99
THE IDEF1X NOTATION 100
THE INFORMATION ENGINEERING NOTATION 104
THE CHEN NOTATION 104
COMPARISON OF THE NOTATIONS 107
8 THE NAMING OF ARTEFACTS ON INFORMATION MODELS 108
THE NAMING OF ENTITY TYPES OR OBJECT CLASSES 108
THE NAMING OF DOMAINS 110
THE NAMING OF ATTRIBUTES 110
THE NAMING OF RELATIONSHIPS IN ELLIS-BARKER ENTITY RELATIONSHIP MODELS 112
THE NAMING OF ASSOCIATIONS ON UML CLASS MODELS 112
9 INFORMATION MODEL QUALITY 114
GENERICITY AND SPECIFICITY IN MODELS 114
THE NINE CHARACTERISTICS OF A GOOD DATA MODEL 116
THE SIX PRINCIPLES OF HIGH QUALITY DATA MODELS 118
THE FIVE DIMENSIONS OF DATA MODEL QUALITY 120
THE LAYOUT OF MODELS 121
10 CORPORATE INFORMATION AND DATA MODELS 123
THE PROBLEMS 123
PRINCIPLES FOR THE DEVELOPMENT OF A CORPORATE MODEL 125
11 DATA AND DATABASES 127
THE DATA LANDSCAPE 127
DATABASES 130
12 BUSINESS INTELLIGENCE 139
THE DATA WAREHOUSE 139
THE MULTIDIMENSIONAL MODEL OF DATA 140
DIMENSIONAL MODELLING 141
13 ADVANCES IN SQL (OR WHY BUSINESS ANALYSTS SHOULD NOT BE IN THE WEEDS) 144
THE BASICS OF SQL 144
NEW SQL DATA TYPES 145
THE FUTURE 151
IMPLICATIONS FOR BUSINESS ANALYSTS AND INFORMATION MODELLERS 151
14 TAKING A REQUIREMENTS INFORMATION MODEL INTO DATABASE DESIGN 154
FIRST-CUT DATABASE DESIGN STAGE 154
OPTIMISED DATABASE DESIGN STAGE 155
APPENDICES 157
APPENDIX A:\tTABLE OF EQUIVALENCES 158
APPENDIX B:\tBIBLIOGRAPHY 159
APPENDIX C:\t\x07SOLUTIONS TO THE EXERCISES 162
INDEX 172
Back Cover 176