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
Table of contents
- Praise for Thinking with Data
- 1. Scoping: Why Before How
- 2. What Next?
- 3. Arguments
- 4. Patterns of Reasoning
- 5. Causality
- 6. Putting It All Together
- A. Further Reading
- Title: Thinking with Data
- Release date: January 2014
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9781491949771
You might also like
Thinking with Data
Data Science draws heavily on statistics, machine learning and software engineering, but these disciplines aren't much …
Communicating with Data
Data is a fantastic raw resource for powering change in an organization, but all too often …
Designing with Data
On the surface, design practices and data science may not seem like obvious partners. But these …
Data Science for Business
Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces …