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Monetizing Your Data Through Decision Architecture and Guided Analytics.
Transforming data into revenue generating strategies and actions Organizations are swamped with data--collected from web traffic, point of sale systems, enterprise resource planning systems, and more , but what to do with it? Monetizing your Data provides a framework and path for business managers t...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Somerset :
John Wiley & Sons, Incorporated,
2017.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Cover
- Title Page
- Copyright
- Contents
- Preface
- Acknowledgments
- About the Authors
- Section I: Introduction
- Chapter 1: Introduction
- Decisions
- Analytical Journey
- Solving the Problem
- The Survey Says ...
- How to Use This Book
- Let's Start
- Chapter 2: Analytical Cycle: Driving Quality Decisions
- Analytical Cycle Overview
- Hierarchy of Information User
- Next Steps
- Chapter 3: Decision Architecture Methodology: Closing the Gap
- Methodology Overview
- Discovery
- Decision Analysis
- Monetization Strategy
- Agile Analytics
- Enablement
- Summary
- Section II: Decision Analysis
- Chapter 4: Decision Analysis: Architecting Decisions
- Category Tree
- Question Analysis
- Key Decisions
- Data Needs
- Action Levers
- Success Metrics
- Category Tree Revisited
- Summary
- Section III: Monetization Strategy
- Chapter 5: Monetization Strategy: Making Data Pay
- Business Levers
- Monetization Strategy Framework
- Decision Analysis and Agile Analytics
- Competitive and Market Information
- Summary
- Chapter 6: Monetization Guiding Principles: Making It Solid
- Quality Data
- Be Specific
- Be Holistic
- Actionable
- Decision Matrix
- Grounded in Data Science
- Monetary Value
- Confidence Factor
- Measurable
- Motivation
- Organizational Culture
- Drives Innovation
- Chapter 7: Product Profitability Monetization Strategy: A Case Study
- Background
- Business Levers
- Discovery
- Decide
- Data Science
- Monetization Framework Requirements
- Decision Matrix
- Section IV: Agile Analytics
- Chapter 8: Decision Theory: Making It Rational
- Decision Matrix
- Probability
- Prospect Theory
- Choice Architecture
- Cognitive Bias
- Chapter 9: Data Science: Making It Smart
- Metrics
- Thresholds
- Trends and Forecasting
- Correlation Analysis
- Segmentation
- Cluster Analysis.
- Velocity
- Predictive and Explanatory Models
- Machine Learning
- Chapter 10: Data Development: Making It Organized
- Data Quality
- Dirty Data, Now What?
- Data Types
- Data Organization
- Data Transformation
- Summary
- Chapter 11: Guided Analytics: Making It Relevant
- So, What?
- Guided Analytics
- Summary
- Chapter 12: User Interface (UI): Making It Clear
- Introduction to UI
- The Visual Palette
- Less Is More
- With Just One Look
- Gestalt Principles of Pattern Perception
- Putting It All Together
- Summary
- Chapter 13: User Experience (UX): Making It Work
- Performance Load
- Go with the Flow
- Modularity
- Propositional Density
- Simplicity on the Other Side of Complexity
- Summary
- Section V: Enablement
- Chapter 14: Agile Approach: Getting Agile
- Agile Development
- Riding the Wave
- Agile Analytics
- Summary
- Chapter 15: Enablement: Gaining Adoption
- Testing
- Adoption
- Summary
- Chapter 16: Analytical Organization: Getting Organized
- Decision Architecture Team
- Decision Architecture Roles
- Subject Matter Experts
- Analytical Organization Mindset
- Section VI: Case Study
- Case Study: Michael Andrews Bespoke
- Discovery
- Decision Analysis Phase
- Monetization Strategy, Part I
- Agile Analytics
- Monetization Strategy, Part II
- Guided Analytics
- Closing
- Bibliography
- Index
- EULA.