Principles of Strategic Data Science describes a framework that creates value from data to help organizations meet their objectives. With this book, you'll bridge the gap between mathematics and computer science and also gain insight into the workings of the entire data science pipeline.

• Cover
• FM
• Copyright
• Table of Contents
• Preface
• Chapter 1: What is Data Science?
  • Introduction
  • Data-Driven Organization
  • The Data Revolution
  • The Elements of Data Science
    • Domain Knowledge
    • Mathematical Knowledge
    • Computer Science
    • The Unicorn Data Scientist?
  • The Purpose of Data Science
• Chapter 2: Good Data Science
  • Introduction
  • A Data Science Trivium
  • Useful Data Science
    • Reality
    • Data
    • Information
    • Knowledge
    • The Feedback Loop
  • Sound Data Science
    • Validity
    • Reliability
    • Reproducibility
    • Governance
  • Aesthetic Data Science
    • Visualization
    • Reports
  • Best-Practice Data Science
• Chapter 3: Strategic Data Science
  • Introduction
  • The Data Science Continuum
  • Collecting Data
  • Descriptive Statistics
    • Business Reporting
  • Diagnostics
    • Qualitative Data Science
  • Predicting the Future
    • Traditional Predictive Methods
    • Machine Learning
  • Prescribing Action
  • Toward a Data-Driven Organization
• Chapter 4: The Data-Driven Organization
  • Introduction
  • People
    • The Data Science Team
    • Data Science Consumers
    • Data Science Culture
  • Systems
  • Process
    • Define
    • Prepare
    • Understand
    • Communicate
  • The Limitations of Data Science
    • The Limits of Computation
    • Ethical Data Science
• References
• Index