Principles of data management : facilitating information sharing

278 Pages·2013·19.344 MB·English

by  Gordon, Keith

PRINCIPLES OF DATA
MANAGEMENT
BCS, THE CHARTERED INSTITUTE FOR IT
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PRINCIPLES OF DATA
MANAGEMENT
FACILITATING INFORMATION
SHARING
Second edition
Keith Gordon
© Keith Gordon 2013
The right of Keith Gordon to be identified as author of this work has been asserted by him in accordance with
Sections 77 and 78 of the Copyright, Designs and Patents Act 1988.
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IT, First Floor, Block D, North Star House, North Star Avenue, Swindon, SN2 1FA, UK.
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Paperback ISBN: 978-1-78017-184-5
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iv
There is nothing more difficult to take in hand, more perilous to conduct, or more uncertain in
its success, than to take the lead in the introduction of a new order of things.
Niccolo Machiavelli (1469–1527)
The beginning of wisdom is the definition of terms.
Socrates (470–399 BC)
Data analysis is a very useful tool for efficient database design. It is much less useful as a means
of identifying information requirements (especially where these are ’fuzzy’ and unstructured),
or in allowing different viewpoints to be taken into consideration. Too often based on an analysis
of current situations, data analysis – in the extreme case – is a great way of encapsulating
organisational ineffectiveness in the resultant database!
Professor Robert Galliers (1947–)
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CONTENTS
List of figures and tables xi
Author xiv
Foreword to the first edition xv
Glossary xvii
Preface xxii
Introduction xxv
PART 1: PRELIMINARIES 1
1. DATA AND THE ENTERPRISE 3
Information is a key business resource 3
The relationship between information and data 4
The importance of the quality of data 6
The common problems with data 7
An enterprise-wide view of data 9
Managing data is a business issue 10
Summary 11
2. DATABASE DEVELOPMENT 12
The database architecture of an information system 12
An overview of the database development process 17
Conceptual data modelling (from a project-level perspective) 22
Relational data analysis 39
The roles of a data model 51
Physical database design 52
Summary 55
3. WHAT IS DATA MANAGEMENT? 57
The problems encountered without data management 57
Data management responsibilities 59
Data management activities 60
Roles within data management 63
The benefits of data management 64
The relationship between data management and enterprise 65
architecture
Summary 66
vii
PRINCIPLES OF DATA MANAGEMENT
PART 2: DATA ADMINISTRATION 67
4. CORPORATE DATA MODELLING 69
Why develop a corporate data model? 69
The nature of a corporate data model 70
How to develop a corporate data model 72
Corporate data model principles 74
Summary 78
5. DATA DEFINITION AND NAMING 80
The elements of a data definition 80
Data naming conventions 84
Summary 86
6. METADATA 87
What is metadata? 87
Metadata for data management 87
Metadata for content management 88
Metadata for describing data values 89
Summary 90
7. DATA QUALITY 91
What is data quality? 91
Issues associated with poor data quality 91
The causes of poor data quality 92
The dimensions of data quality 93
Data model quality 94
Improving data quality 95
Summary 98
8. DATA ACCESSIBILITY 99
Data security 99
Data integrity 104
Data recovery 106
Summary 108
9. MASTER DATA MANAGEMENT 109
What is master data? 109
How do problems with master data occur? 112
How do we manage master data? 112
Summary 114
PART 3: DATABASE AND REPOSITORY ADMINISTRATION 115
10. DATABASE ADMINISTRATION 117
Database administration responsibilities 117
Performance monitoring and tuning 119
Summary 120
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