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Thinking with Data: How to Turn Information Into Insights

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Thinking with Data: How to Turn Information Into Insights Cover

 

Synopses & Reviews

Publisher Comments:

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. Youll 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. Youll 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

Synopsis:

Understanding how to turn numbers into usable insights is a significant challenge for those who work with data on a daily basis. Thinking with Data provides a concise framework and key insights to help data people uncover the real problem to be solved as well as how to approach, organize, and analyze potential results.

Author Max Shron draws from rhetoric studies, design thinking, and his data strategy consultancy experience to help you understand how focusing on the why will help you create usable insights from your company's data jumble.

  • 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

About the Author

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.

Product Details

ISBN:
9781449362935
Author:
Shron, Max
Publisher:
O'Reilly Media
Subject:
Data Modeling & Design
Subject:
analysis;analytics;critical thinking;data;design thinking;thinking,
Subject:
Database design
Edition Description:
Print PDF
Publication Date:
20140231
Binding:
TRADE PAPER
Language:
English
Pages:
94
Dimensions:
9 x 6 in

Related Subjects

» Computers and Internet » Computers Reference » General
» Computers and Internet » Database » Design
» Engineering » Engineering » Project Management
» Languages » ESL » General

Thinking with Data: How to Turn Information Into Insights New Trade Paper
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$30.95 In Stock
Product details 94 pages O'Reilly Media - English 9781449362935 Reviews:
"Synopsis" by ,

Understanding how to turn numbers into usable insights is a significant challenge for those who work with data on a daily basis. Thinking with Data provides a concise framework and key insights to help data people uncover the real problem to be solved as well as how to approach, organize, and analyze potential results.

Author Max Shron draws from rhetoric studies, design thinking, and his data strategy consultancy experience to help you understand how focusing on the why will help you create usable insights from your company's data jumble.

  • 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

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