"How to Turn Information into Insights"-- en la portada

Max Shron runs a small data strategy consultancy in New York, working with many organizations to help them get the most out of their data. His analyses of transit, public health, and housing markets has been featured in The New York Times, Chicago Tribune, Huffington Post, WNYC, and more. Prior to becoming a data strategy consultant, he was the data scientist for OkCupid.

Incluye: bibliografia recomendada paginas 77-78

1. Chapter 1: Scoping: Why Before How -- Context (Co) -- Needs (N) -- Vision (V) -- Outcome (O) -- Seeing the Big Picture -- Chapter 2: What Next? -- Refining the Vision -- Deep Dive: Real Estate and Public Transit -- Deep Dive Continued: Working Forward -- Deep Dive Continued: Scaffolding -- Verifying Understanding -- Getting Our Hands Dirty -- Chapter 3: Arguments -- Audience and Prior Beliefs -- Claims -- Evidence, Justification, and Rebuttals -- Deep Dive: Improving College Graduation Rates -- Chapter 4: Patterns of Reasoning -- Categories of Disputes -- General Topics -- Special Arguments -- Chapter 5: Causality -- Defining Causality -- Designs -- Intervention Designs -- Observational Designs -- Natural Experiments -- Statistical Methods -- Chapter 6: Putting It All Together -- Deep Dive: Predictive Model for Conversion Probability -- Deep Dive: Calculating Access to Microfinance -- Wrapping Up -- Appendix Further Reading

"Many analysts are too concerned with tools and techniques for cleansing, modeling, and visualizing datasets and not concerned enough with asking the right questions. In this practical guide, data strategy consultant Max Shron shows you how to put the why before the how , through an often-overlooked set of analytical skills. Thinking with Data helps you learn techniques for turning data into knowledge you can use. You'll learn a framework for defining your project, including the data you want to collect, and how you intend to approach, organize, and analyze the results. You'll also learn patterns of reasoning that will help you unveil the real problem that needs to be solved. Learn a framework for scoping data projects Understand how to pin down the details of an idea, receive feedback, and begin prototyping Use the tools of arguments to ask good questions, build projects in stages, and communicate results Explore data-specific patterns of reasoning and learn how to build more useful arguments Delve into causal reasoning and learn how it permeates data work Put everything together, using extended examples to see the method of full problem thinking in action."-- P. 4

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