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Information–Driven Business. How to Manage Data and Information for Maximum Advantage

  • ID: 2243052
  • Book
  • September 2010
  • 240 Pages
  • John Wiley and Sons Ltd
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Praise for Information–Driven Business How to Manage Data and Information for Maximum Advantage

"Robert Hillard gets it! The sheer quantity of information that is descending upon our organizations means that we can′t just ′wing it′ when it comes to managing information. The strategic imperative to manage information effectively is now irreversible with devastating consequences for those who assume it is otherwise. The book provides you with a thorough understanding of how to find, control, and optimize your information assets."
Atle Skjekkeland, Vice President, The Association for Information and Image Management (AIIM)

"Information–Driven Business takes a highly complex subject like information theory and makes it far more accessible for the general reader. It is truly a call to action for an effective transition to the new information economy. If you are a student preparing to join the workforce, a seasoned information management professional, or an executive looking to make your business thrive through better information, you′ll benefit from Hillard′s innovative thinking and pragmatic recommendations."
Sean McClowry, Senior Vice President, Knowledge Management, Global Carbon Capture and Storage Institute

"The book brilliantly combines a broad historical view of information management foundations with cutting–edge advances in information governance, including the notion of Economic Value of Information the author pioneered. Information governance metrics: what are they? The book provides some unique answers to this very important question. This is a great book for business executives, information technology professionals, and others who want to better understand the role of information in our society and for the corporate world."
Lawrence Dubov, PhD, coauthor of Master Data Management and Customer Data Integration for a Global Enterprise

Information doesn′t just tell you about your business.
It is your business.

As data becomes more and more prevalent in businesses, leaders must find ways to leverage this asset. Even businesses that are traditionally associated with manufacturing products are increasingly concerned with maintaining their intellectual property.

Information–Driven Business helps you understand this change and find the hidden value in your data. Author and information management leader Robert Hillard explains the techniques your business can apply immediately and provides the foundation on which analytical and data–rich organizations can be created.

Innovative and revealing, this essential book unveils how you can more effectively govern, manage, and exploit your company′s most important asset, information, with workable solutions to real business problems and virtually instant benefits.

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Preface xiii

Acknowledgments xv

Chapter 1: Understanding the Information Economy 1

Did the Internet Create the Information Economy? 2

Origins of Electronic Data Storage 2

Stocks and Flows 3

Business Data 4

Changing Business Models 5

Information Sharing versus Infrastructure Sharing 6

Governing the New Business 7

Success in the Information Economy 8

Notes 9

Chapter 2: The Language of Information 10

Structured Query Language 13

Statistics 14

XQuery Language 15

Spreadsheets 15

Documents and Web Pages 16

Knowledge, Communications, and Information Theory 17

Notes 18

Chapter 3: Information Governance 19

Information Currency 19

Economic Value of Data 21

Goals of Information Governance 23

Organizational Models 24

Ownership of Information 26

Strategic Value Models 27

Repackaging of Information 30

Life Cycle 31

Notes 32

Chapter 4: Describing Structured Data 33

Networks and Graphs 33

Brief Introduction to Graphs 35

Relational Modeling 37

Relational Concepts 38

Cardinality and Entity–Relationship Diagrams 39

Normalization 40

Impact of Time and Date on Relational Models 49

Applying Graph Theory to Data Models 51

Directed Graphs 52

Normalized Models 53

Note 54

Chapter 5: Small Worlds Business Measure of Data 55

Small Worlds 55

Measuring the Problem and Solution 56

Abstracting Information as a Graph 57

Metrics 58

Interpreting the Results 60

Navigating the Information Graph 61

Information Relationships Quickly Get Complex 62

Using the Technique 64

Note 65

Chapter 6: Measuring the Quantity of Information 66

Definition of Information 66

Thermal Entropy 67

Information Entropy 68

Entropy versus Storage 70

Enterprise Information Entropy 73

Decision Entropy 76

Conclusion and Application 78

Notes 78

Chapter 7: Describing the Enterprise 79

Size of the Undertaking 79

Enterprise Data Models Are All or Nothing 80

The Data Model as a Panacea 81

Metadata 82

The Metadata Solution 83

Master Data versus Metadata 84

The Metadata Model 85

XML Taxonomies 87

Metadata Standards 87

Collaborative Metadata 88

Metadata Technology 90

Data Quality Metadata 91

History 91

Executive Buy–in 92

Notes 93

Chapter 8: A Model for Computing Based on Information Search 94

Function–Centric Applications 95

An Information–Centric Business 96

Enterprise Search 97

Security 98

Metadata Search Repository 98

Building the Extracts 100

The Result 100

Note 102

Chapter 9: Complexity, Chaos, and System Dynamics 103

Early Information Management 103

Simple Spreadsheets 104

Complexity 105

Chaos Theory 105

Why Information Is Complex 106

Extending a Prototype 110

System Dynamics 112

Data as an Algorithm 116

Virtual Models and Integration 118

Chaos or Complexity 119

Notes 120

Chapter 10: Comparing Data Warehouse Architectures 121

Data Warehousing 121

Contrasting the Inmon and Kimball Approaches 122

Quantity Implications 123

Usability Implications 125

Historical Data 132

Summary 133

Notes 134

Chapter 11: Layered View of Information 135

Information Layers 136

Are They Real? 137

Turning the Layers into an Architecture 141

The User Interface 143

Selling the Architecture 144

Chapter 12: Master Data Management 146

Publish and Subscribe 146

About Time 148

Granularity, Terminology, and Hierarchies 148

Rule 1: Consistent Terminology 149

Rule 2: Everyone Owns the Hierarchies 150

Rule 3: Consistent Granularity 150

Reconciling Inconsistencies 151

Slowly Changing Dimensions 151

Customer Data Integration 153

Extending the Metadata Model 153

Technology 155

Chapter 13: Information and Data Quality 156

Spreadsheets 156

Referencing 157

Fit for Purpose 158

Measuring Structured Data Quality 160

A Scorecard 164

Metadata Quality 164

Extended Metadata Model 165

Notes 166

Chapter 14: Security 167

Cryptography 167

Public Key Cryptography 169

Applying PKI 170

Predicting the Unpredictable 172

Protecting an Individual s Right to Privacy 172

Securing the Content versus Securing the Reference 175

Chapter 15: Opening Up to the Crowd 176

A Taxonomy for the Future 177

Populating the Stakeholder Attributes 179

Reducing E–mail Traffic within Projects 179

Managing Customer E–mail 180

General E–mail 180

Preparing for the Unknown 181

Third–Party Data Charters 182

Information Is Dynamic 183

Power of the Crowd Can Improve Your Data Quality 183

Note 184

Chapter 16: Building Incremental Knowledge 185

Bayesian Probabilities 187

Information from Processes 188

The MIT Beer Game 192

Hypothesis Testing and Confidence Levels 193

Business Activity Monitoring 195

Note 196

Chapter 17: Enterprise Information Architecture 197

Web Site Information Architecture 198

Extending the Information Architecture 198

Business Context 199

Users 199

Content 200

Top–Down/Bottom–Up 200

Presentation Format 201

Project Resourcing 201

Information to Support Decision Making 203

Notes 204

Looking to the Future 205

About the Author 209

Index 211

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Robert Hillard
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