Thinking with Data
How to Turn Information into Insights
Publisher: O'Reilly Media
Final Release Date: January 2014
Pages: 94

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
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About the Author
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oreillyThinking with Data
 
4.2

(based on 5 reviews)

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100%

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Pros

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  • Accurate (3)

Cons

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      5.0

      The missing link

      By Raanan

      from Israel

      Pros

      • Accurate
      • Easy to understand
      • Well-written

      Cons

        Best Uses

          Comments about oreilly Thinking with Data:

          The Data Scientist education is almost always about the data and the algorithms and never about the context of the data.

          This should be a course of it's own in any Data Scientist education program.

           
          4.0

          Gives you another tool to prove your poi

          By retired techie

          from Sarnia Ontario Canada

          Verified Buyer

          Pros

          • Easy to understand

          Cons

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              Comments about oreilly Thinking with Data:

              This makes sense to those who already use logic in their thinking. It is helpful to present logic to others.

              (1 of 1 customers found this review helpful)

               
              4.0

              Solid Principles in Data Analytics

              By Vinitor

              from Rochester, New York

              About Me Developer, Educator, Sys Admin

              Verified Reviewer

              Pros

              • Accurate
              • Concise
              • Easy to understand
              • Helpful examples
              • Well-written

              Cons

                Best Uses

                • Intermediate
                • Novice
                • Student

                Comments about oreilly Thinking with Data:

                Max Shron nails it. Until we can clearly articulate the needs we are trying to meet, and how to meet them, we do not fully understand what we hope to do. Sharon takes you through the process. By explaining the need not only for good data, but good questions and good methods. The solutions are available, if we understand what to look for, and to understand the solution.

                With scenarios discussed throughout, Shron gives you tools to gain insight and objectivity when evaluating. After reading, finding the correct space for analysis, process and strategy will develop. Understanding the development of data, is necessary. However, the real gain is interpreting data in proper terms of origin, and applying solid statistical methods revealing the predictive power.

                I would recommend this book for evaluating data to solve problems for any project.

                (7 of 8 customers found this review helpful)

                 
                4.0

                Great For Everyone - Not Just For Data R

                By alanklement

                from New York

                Verified Reviewer

                Comments about oreilly Thinking with Data:

                This book is no longer than it needs to be and the title for 1 of it's 6 chapters is 'Causality' - how could I NOT like this book!

                I highly recommend this book to anyone who is involved in the development of software products. This is because above all else, it's book about critical thinking within the context of product - and even more specifically, how to use Data to improve our products.

                This book sits in a sweet spot of being high level enough to keep the content flowing as well as peppering it with pin point examples that succinctly illustrate the author's point. The author doesn't waste words overemphasizing points or tying concpets to any specific engineering or project management discipline. This should be appreciated as it respects both the reader's intelligence and time.

                If your a product manager, engineer, designer...or anyone else involved in creating and growing products, I recommend this book to you.

                Here is an excerpt which conveys my point. This is from Chapter 1 - Scoping: Why Before How:

                "...Rather than saying, "The manager wants to know where users drop out on the way to buying something," consider saying, "The manager wants more users to finish their purchases. How do we encourage that?" Answering the first question is a component of doing the second, but the action-oriented formulation opens up more possibilities, such as testing new designs and performing user experience interviews to gather more data.

                If it is not helpful to phrase something in terms of an action, it should at least be related to some larger strategic question. For example, understanding how users of a product are migrating from desktop to mobile versions of a website is useful for informing the product strategy, even if there is no obvious action to take afterward..."

                Also, there's no online table of contents for this book so here it is:

                1. Scoping: Why Before How
                2. What's Next?
                3. Arguments
                4. Patterns of Reasoning
                5. Causality
                6. Putting It All Together
                A. Further Reading

                (3 of 4 customers found this review helpful)

                 
                4.0

                Knowledge southward, data northward

                By vivian

                from hyderabad, india

                About Me Educator, Maker, Very Easy Read

                Verified Reviewer

                Pros

                • Accurate
                • Easy Read
                • Easy to understand

                Cons

                • Too short

                Best Uses

                • Analysts
                • Intermediate
                • Novice

                Comments about oreilly Thinking with Data:

                as data grows exponentially due to multiple phenomenon like online socialization, integration of entertainment telecom and media etc, the data management has become the most serious problem and businesses across the world need to through data to survive in ever increasing competition. "thinking with data" brings a clarity on the thinking pattern we need to follow to create knowledge from data. A must read for business analysts globally.

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