Thinking with Data

By (author)Max Shron
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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


“Thinking with Data gets to the essence of the process, and guides data scientists in answering
that most important question—what’s the problem we’re really trying to solve?”
— Hilary Mason
Data Scientist in Residence at Accel Partners; co-founder of
the DataGotham Conference


“Thinking with Data does a wonderful job of reminding data scientists to look past technical
issues and to focus on making an impact on the broad business objectives of their employers
and clients. It’s a useful supplement to a data science curriculum that is largely focused on
the technical machinery of statistics and computer science.”
— John Myles White
Scientist at Facebook; author of Machine Learning for
Hackers and Bandit Algorithms for Website Optimization






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