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1 Data and the Enterprise
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1 Data and the Enterprise
by Gordon Keith
Principles of Data Management
Copyright
Dedication
Figures and tables
About the author
Foreword
Glossary
Preface
Introduction
1 Data and the Enterprise
INFORMATION IS A KEY BUSINESS RESOURCE
THE RELATIONSHIP BETWEEN INFORMATION AND DATA
THE IMPORTANCE OF THE QUALITY OF DATA
THE COMMON PROBLEMS WITH DATA
AN ENTERPRISE-WIDE VIEW OF DATA
MANAGING DATA IS A BUSINESS ISSUE
SUMMARY
2 Database Development
THE DATABASE ARCHITECTURE OF AN INFORMATION SYSTEM
AN OVERVIEW OF THE DATABASE DEVELOPMENT PROCESS
CONCEPTUAL DATA MODELLING (FROM A PROJECT-LEVEL PERSPECTIVE)
RELATIONAL DATA ANALYSIS
THE ROLES OF A DATA MODEL
PHYSICAL DATABASE DESIGN
SUMMARY
3 What is Data Management?
THE PROBLEMS ENCOUNTERED WITHOUT DATA MANAGEMENT
DATA MANAGEMENT RESPONSIBILITIES
ROLES WITHIN DATA MANAGEMENT
THE BENEFITS OF DATA MANAGEMENT
THE RELATIONSHIP BETWEEN DATA MANAGEMENT AND ENTERPRISE ARCHITECTURE
SUMMARY
4 Corporate Data Modelling
WHY DEVELOP A CORPORATE DATA MODEL?
MORE DATA MODELLING CONCEPTS
THE NATURE OF A CORPORATE DATA MODEL
HOW TO DEVELOP A CORPORATE DATA MODEL
CORPORATE DATA MODEL PRINCIPLES
A FINAL THOUGHT
SUMMARY
5 Data Definition and Naming Conventions
THE ELEMENTS OF A DATA DEFINITION
DATA NAMING CONVENTIONS
SUMMARY
6 Metadata
WHAT IS METADATA?
METADATA FOR DATA MANAGEMENT
METADATA FOR CONTENT MANAGEMENT
METADATA FOR DESCRIBING DATA VALUES
SUMMARY
7 Data Quality
WHAT IS DATA QUALITY?
ISSUES ASSOCIATED WITH POOR-QUALITY DATA
THE CAUSES OF POOR-QUALITY DATA
THE DIMENSIONS OF DATA QUALITY
DATA MODEL QUALITY
IMPROVING DATA QUALITY
SUMMARY
8 Data Accessibility
DATA SECURITY
DATA INTEGRITY
DATA RECOVERY
SUMMARY
9 Database Administration
DATABASE ADMINISTRATION RESPONSIBILITIES
PERFORMANCE MONITORING AND TUNING
SUMMARY
10 Repository Administration
REPOSITORIES, DATA DICTIONARIES, ENCYCLOPAEDIAS, CATALOGS AND DIRECTORIES
REPOSITORY FEATURES
THE REPOSITORY AS A CENTRALISED SOURCE OF INFORMATION
METADATA MODELS
SUMMARY
11 The Management of Data Management
TECHNIQUES AND SKILLS FOR DATA ADMINISTRATION
TECHNIQUES AND SKILLS FOR DATABASE ADMINISTRATION
TECHNIQUES AND SKILLS FOR REPOSITORY ADMINISTRATION
THE POSITIONING OF DATA MANAGEMENT WITHIN THE ENTERPRISE
SUMMARY
12 Industry Trends and their Effects on Data Management
THE USE OF PACKAGES
DISTRIBUTED DATA AND DATABASES
DATA WAREHOUSING AND DATA MINING
OLAP
OBJECT ORIENTATION AND DATABASES
MULTIMEDIA AND DATABASES
DATA AND WEB TECHNOLOGY
SUMMARY
Appendix A Comparison of Data Modelling Notations
The Ellis-Barker notation
The Chen notation
The information engineering notation
The IDEF1X notation
The UML class notation
Comparison of the notations
Appendix B Hierarchical and Network Databases
Hierarchical databases
Network databases
Appendix C Generic Data Models
Appendix D An Example of a Data Naming Convention
Introduction
Concepts used in naming
The naming of entity types in a conceptual data model
The naming of domains in a conceptual data model
The naming of attributes in a conceptual data model
The naming of relationships in a conceptual data model
The naming of tables in an SQL logical schema
The naming of columns in an SQL logical schema
Rules for abbreviations in data names
Restricted terms
The naming of attributes: a formal description
Appendix E Metadata Models
Introduction
Metadata model to record conceptual data models
Metadata model to record SQL logical schemas
Metadata model to support the mapping of concepts
The inclusion of processes
Appendix F A Data Mining Example
Introduction
The scenario
Step 1
Step 2
Step 3
Step 4
Step 5
Step 6
Conclusions
Appendix G HTML and XML
Introduction
HTML
HTML
Appendix H XML and Relational Databases
Introduction
Representing data from a database as XML
Extracting relational data from an XML document
REFERENCES
FURTHER READING
Index
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Introduction
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INFORMATION IS A KEY BUSINESS RESOURCE
This chapter introduces the concepts of information and data and discusses why they are important business resources within the enterprise. The problems caused by data which is of poor quality or is inconsistent are introduced.
1 Data and the Enterprise
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