Book contents
- Insight-Driven Problem Solving
- Insight-Driven Problem Solving
- Copyright page
- Dedication
- Contents
- Preface
- Introduction
- 1 The Big Picture of Analytics Science
- 2 Artificial Intelligence and Machine Learning
- 3 Queueing Theory and Resource Allocation
- 4 Game Theory and Mechanism Design
- 5 Linear and Nonlinear Mathematical Programming
- 6 Dynamic Programming and Sequential Decision-Making
- 7 Data Analysis
- 8 Graph Theory, Combinatorial Optimization, and Supply Chains
- Acknowledgments
- Notes
- References
- Index
1 - The Big Picture of Analytics Science
Published online by Cambridge University Press: 21 October 2025
Book contents
- Insight-Driven Problem Solving
- Insight-Driven Problem Solving
- Copyright page
- Dedication
- Contents
- Preface
- Introduction
- 1 The Big Picture of Analytics Science
- 2 Artificial Intelligence and Machine Learning
- 3 Queueing Theory and Resource Allocation
- 4 Game Theory and Mechanism Design
- 5 Linear and Nonlinear Mathematical Programming
- 6 Dynamic Programming and Sequential Decision-Making
- 7 Data Analysis
- 8 Graph Theory, Combinatorial Optimization, and Supply Chains
- Acknowledgments
- Notes
- References
- Index
Summary
This chapter introduces the reader to the big picture of what analytics science is. What is analytics science? What types does it have, and what is its scope? How can analytics science be used to improve various tasks that society needs to carry out? Is analytics science all about using data? Or can it work without data? What is the role of data versus models? How can one develop and rely on a model to answer essential questions when the model can be wrong due to its assumptions? What is ambiguity in analytics science? Is that different from risk? And how do analytics scientists address ambiguity? What is the role of simulation in analytics science? These are some of the questions that the chapter addresses. Finally, the chapter discusses the notion of "centaurs" and how a successful use of analytics science often requires combining human intuition with the power of strong analytical models.
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- Insight-Driven Problem SolvingAnalytics Science to Improve the World, pp. 12 - 52Publisher: Cambridge University PressPrint publication year: 2025
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