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

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 business 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.

Spis treści:
Preface.
Acknowledgments.
Chapter 1: Understanding the Information Economy.
Did the Internet Create the Information Economy?
Origins of Electronic Data Storage.
Stocks and Flows.
Business Data.
Changing Business Models.
Information Sharing versus Infrastructure Sharing.
Governing the New Business.
Success in the Information Economy.
Note.
Chapter 2: The Language of Information.
Structured Query Language.
Statistics.
XQuery Language.
Spreadsheets.
Documents and Web Pages.
Knowledge, Communications, and Information Theory.
Notes.
Chapter 3: Information Governance.
Information Currency.
Economic Value of Data.
Goals of Information Governance.
Organizational Models.
Ownership of Information.
Strategic Value Models.
Repackaging of Information.
Lifecycle.
Notes.
Chapter 4: Describing Structured Data.
Networks and Graphs.
Brie f Introduction to Graphs.
Relational Modeling.
Relational Concepts.
Cardinality and Entity–Relationship Diagrams.
Normalization.
Impact of Time and Date on Relational Models.
Applying Graph Theory to Data Models.
Directed Graphs.
Normalized Models.
Note.
Chapter 5: Small Worlds Business Measure of Data.
Small Worlds.
Measuring the Problem and Solution.
Abstracting Information as a Graph.
Metrics.
Interpreting the Results.
Navigating the Information Graph.
Information Relationships Quickly Get Complex.
Using the Technique.
Note.
Chapter 6: Measuring the Quantity of Information.
Definition of Information.
Thermal Entropy.
Information Entropy.
Entropy versus Storage.