Information-Driven Business How to Manage Data and Information for Maximum Advantage

by Hillard, Robert

• ISBN13: 9780470625774
• ISBN10: 0470625775
• Edition: 1st
• Format: Hardcover
• Copyright: 2010-08-23
• Publisher: Wiley
• More Book Details

Summary

Information doesn't just provide a window on the business, increasingly it is the business. The global economy is moving from products to services which are described almost entirely electronically. Even those businesses that are traditionally associated with making things are less concerned with managing the manufacturing process (which is largely outsourced) than they are with maintaining their intellectual property.Information-Driven Business helps you to understand this change and find the value in your data. Hillard explains techniques that organizations can use and how businesses can apply them immediately. For example, simple changes to the way data is described will let staff support their customers much more quickly; and two simple measures let executives know whether they will be able to use the content of a database before it is even built. This book provides the foundation on which analytical and data rich organizations can be created.Innovative and revealing, this book provides a robust description of Information Management theory and how you can pragmatically apply it to real business problems, with almost instant benefits. Information-Driven Business comprehensively tackles the challenge of managing information, starting with why information has become important and how it is encoded, through to how to measure its use.

Author Biography

ROBERT HILLARD is an original founder of MIKE2.0 (www.openmethodology.org), which provides a standard approach for information and data management projects. He has held international consulting leadership roles and provided advice to government and private sector clients around the world. He is a partner with Deloitte with more than twenty years' experience in the discipline, focusing on standardized approaches to information management, including being one of the first to use XBRL in government regulation and the promotion of information as a business asset rather than a technology problem. Find out more at www.infodrivenbusiness.com.

Table of Contents

Preface	p. xiii
Acknowledgments	p. xv
Understanding the Information Economy	p. 1
Did the Internet Create the Information Economy?	p. 2
Origins of Electronic Data Storage	p. 2
Stocks and Flows	p. 3
Business Data	p. 4
Changing Business Models	p. 5
Information Sharing versus Infrastructure Sharing	p. 6
Governing the New Business	p. 7
Success in the Information Economy	p. 8
Notes	p. 9
The Language of Information	p. 10
Structured Query Language	p. 13
Statistics	p. 14
XQuery Language	p. 15
Spreadsheets	p. 15
Documents and Web Pages	p. 16
Knowledge, Communications, and Information Theory	p. 17
Notes	p. 18
Information Governance	p. 19
Information Currency	p. 19
Economic Value of Data	p. 21
Goals of Information Governance	p. 23
Organizational Models	p. 24
Ownership of Information	p. 26
Strategic Value Models	p. 27
Repackaging of Information	p. 30
Life Cycle	p. 31
Notes	p. 32
Describing Structured Data	p. 33
Networks and Graphs	p. 33
Brief Introduction to Graphs	p. 35
Relational Modeling	p. 37
Relational Concepts	p. 38
Cardinality and Entity-Relationship Diagrams	p. 39
Normalization	p. 40
Impact of Time and Date on Relational Models	p. 49
Applying Graph Theory to Data Models	p. 51
Directed Graphs	p. 52
Normalized Models	p. 53
Note	p. 54
Small Worlds Business Measure of Data	p. 55
Small Worlds	p. 55
Measuring the Problem and Solution	p. 56
Abstracting Information as a Graph	p. 57
Metrics	p. 58
Interpreting the Results	p. 60
Navigating the Information Graph	p. 61
Information Relationships Quickly Get Complex	p. 62
Using the Technique	p. 64
Note	p. 65
Measuring the Quantity of Information	p. 66
Definition of Information	p. 66
Thermal Entropy	p. 67
Information Entropy	p. 68
Entropy versus Storage	p. 70
Enterprise Information Entropy	p. 73
Decision Entropy	p. 76
Conclusion and Application	p. 78
Notes	p. 78
Describing the Enterprise	p. 79
Size of the Undertaking	p. 79
Enterprise Data Models Are All or Nothing	p. 80
The Data Model as a Panacea	p. 81
Metadata	p. 82
The Metadata Solution	p. 83
Master Data versus Metadata	p. 84
The Metadata Model	p. 85
XML Taxonomies	p. 87
Metadata Standards	p. 87
Collaborative Metadata	p. 88
Metadata Technology	p. 90
Data Quality Metadata	p. 91
History	p. 91
Executive Buy-in	p. 92
Notes	p. 93
A Model for Computing Based on Information Search	p. 94
Function-Centric Applications	p. 95
An Information-Centric Business	p. 96
Enterprise Search	p. 97
Security	p. 98
Metadata Search Repository	p. 98
Building the Extracts	p. 100
The Result	p. 100
Note	p. 102
Complexity, Chaos, and System Dynamics	p. 103
Early Information Management	p. 103
Simple Spreadsheets	p. 104
Complexity	p. 105
Chaos Theory	p. 105
Why Information Is Complex	p. 106
Extending a Prototype	p. 110
System Dynamics	p. 112
Data as an Algorithm	p. 116
Virtual Models and Integration	p. 118
Chaos or Complexity	p. 119
Notes	p. 120
Comparing Data Warehouse Architectures	p. 121
Data Warehousing	p. 121
Contrasting the Inmon and Kimball Approaches	p. 122
Quantity Implications	p. 123
Usability Implications	p. 125
Historical Data	p. 132
Summary	p. 133
Notes	p. 134
Layered View of Information	p. 135
Information Layers	p. 136
Are They Real?	p. 137
Turning the Layers into an Architecture	p. 141
The User Interface	p. 143
Selling the Architecture	p. 144
Master Data Management	p. 146
Publish and Subscribe	p. 146
About Time	p. 148
Granularity, Terminology, and Hierarchies	p. 148
Rule 1: Consistent Terminology	p. 149
Rule 2: Everyone Owns the Hierarchies	p. 150
Rule 3: Consistent Granularity	p. 150
Reconciling Inconsistencies	p. 151
Slowly Changing Dimensions	p. 151
Customer Data Integration	p. 153
Extending the Metadata Model	p. 153
Technology	p. 155
Information and Data Quality	p. 156
Spreadsheets	p. 156
Referencing	p. 157
Fit for Purpose	p. 158
Measuring Structured Data Quality	p. 160
A Scorecard	p. 164
Metadata Quality	p. 164
Extended Metadata Model	p. 165
Notes	p. 166
Security	p. 167
Cryptography	p. 167
Public Key Cryptography	p. 169
Applying PKI	p. 170
Predicting the Unpredictable	p. 172
Protecting an Individual's Right to Privacy	p. 172
Securing the Content versus Securing the Reference	p. 175
Opening Up to the Crowd	p. 176
A Taxonomy for the Future	p. 177
Populating the Stakeholder Attributes	p. 179
Reducing E-mail Traffic within Projects	p. 179
Managing Customer E-mail	p. 180
General E-mail	p. 180
Preparing for the Unknown	p. 181
Third-Party Data Charters	p. 182
Information Is Dynamic	p. 183
Power of the Crowd Can Improve Your Data Quality	p. 183
Note	p. 184
Building Incremental Knowledge	p. 185
Bayesian Probabilities	p. 187
Information from Processes	p. 188
The MIT Beer Game	p. 192
Hypothesis Testing and Confidence Levels	p. 193
Business Activity Monitoring	p. 195
Note	p. 196
Enterprise Information Architecture	p. 197
Web Site Information Architecture	p. 198
Extending the Information Architecture	p. 198
Business Context	p. 199
Users	p. 199
Content	p. 200
Top-Down/Bottom-Up	p. 200
Presentation Format	p. 201
Project Resourcing	p. 201
Information to Support Decision Making	p. 203
Notes	p. 204
Looking to the Future	p. 205
About the Author	p. 209
Index	p. 211
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