Monetizing Your Data : A Guide to Turning Data into Profit-Driving Strategies and Solutions.
Kathy Williams. Chiang
Bok Engelsk 2017 · Electronic books.
| Omfang | 1 online resource (369 pages)
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| Opplysninger | 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.
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| Emner | |
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| Dewey | |
| ISBN | 9781119356264
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