Log In
Or create an account ->
Imperial Library
Home
About
News
Upload
Forum
Help
Login/SignUp
Index
Cover
Title Page
Table of Contents
About the Authors
List of Figures
List of Tables
Preface
1 The Opportunity
1.1 Introduction
1.2 The Rise of Data
1.3 Realising Data as an Opportunity
1.4 Our Definition of Monetising Data
1.5 Guidance on the Rest of the Book
2 About Data and Data Science
2.1 Introduction
2.2 Internal and External Sources of Data
2.3 Scales of Measurement and Types of Data
2.4 Data Dimensions
2.5 Quality of Data
2.6 Importance of Information
2.7 Experiments Yielding Data
2.8 A Data‐readiness Scale for Companies
2.9 Data Science
2.10 Data Improvement Cycle
3 Big Data Handling, Storage and Solutions
3.1 Introduction
3.2 Big Data, Smart Data…
3.3 Big Data Solutions
3.4 Operational Systems supporting Business Processes
3.5 Analysis‐based Information Systems
3.6 Structured Data – Data Warehouses
3.7 Poly‐structured (Unstructured) Data – NoSQL Technologies
3.8 Data Structures and Latency
3.9 Data Marts
4 Data Mining as a Key Technique for Monetisation
4.1 Introduction
4.2 Population and Sample
4.3 Supervised and Unsupervised Methods
4.4 Knowledge‐discovery Techniques
4.5 Theory of Modelling
4.6 The Data Mining Process
5 Background and Supporting Statistical Techniques
5.1 Introduction
5.2 Variables
5.3 Key Performance Indicators
5.4 Taming the Data
5.5 Data Visualisation and Exploration of Data
5.6 Basic Statistics
5.7 Feature Selection and Reduction of Variables
5.8 Sampling
5.9 Statistical Methods for Proving Model Quality and Generalisability and Tuning Models
6 Data Analytics Methods for Monetisation
6.1 Introduction
6.2 Predictive Modelling Techniques
6.3 Pattern Detection Methods
6.4 Methods in practice
7 Monetisation of Data and Business Issues: Overview
7.1 Introduction
7.2 General Strategic Opportunities
7.3 Data as a Donation
7.4 Data as a Resource
7.5 Data Leading to New Business Opportunities
7.6 Information Brokering using Data
7.7 Connectivity as a Strategic Opportunity
7.8 Problem‐solving Methodology
8 How to Create Profit Out of Data
8.1 Introduction
8.2 Business Models for Monetising Data
8.3 Data Product Design
8.4 Value of Data
8.5 Charging Mechanisms
8.6 Connectivity as an Opportunity for Streamlining a Business
9 Some Practicalities of Monetising Data
9.1 Introduction
9.2 Practicalities
9.3 Special focus on SMEs
9.4 Special Focus on B2B Lead Generation
9.5 Legal and Ethical Issues
9.6 Payments
9.7 Innovation
10 Case Studies
10.1 Job Scheduling in Utilities
10.2 Shipping
10.3 Online Sales or Mail Order
10.4 Intelligent Profiling with Loyalty Card Schemes
10.5 Social Media: a Mechanism to Collect and Use Contributor Data
10.6 Making a Business out of Boring Statistics
10.7 Social Media and Web Intelligence Services
10.8 Service Provider
10.9 Data Source
10.10 Industry 4.0: Metamodelling using Simulated Data
10.11 Industry 4.0: Modelling Pricing Data in Manufacturing
10.12 Monetising Data in an SME
10.13 Making Sense of Public Finance and Other Data
10.14 Benchmarking who is the Best in the Market
10.15 Change of Shopping Habits Part I
10.16 Change of Shopping Habits Part II
10.17 Change of Shopping Habits Part III
10.18 Service Providers, Households and Facility Management
10.19 Insurance, Healthcare and Risk Management
10.20 Mobility and Connected Cars
10.21 Production and Automation in Industry 4.0
Bibliography
Glossary
Index
End User License Agreement
← Prev
Back
Next →
← Prev
Back
Next →