The Data Loom: Weaving Understanding by Thinking Critically and Scientifically With Data

We rely on "information professionals" to help us understand data, but most fail in their efforts. Why? Not because they lack intelligence or tools, but mostly because they lack the necessary skills. Most information professionals have been trained primarily in the use of data analysis tools (Tableau, PowerBI, Qlik, SAS, Excel, R, etc.), but even the best tools are only useful in the hands of skilled individuals. Anyone can pick up a hammer and pound a nail, but only skilled carpenters can use a hammer to build a reliable structure. Making sense of data is skilled work, and developing those skills requires study and practice.

Weaving data into understanding involves several distinct but complementary thinking skills. Foremost among them are critical thinking and scientific thinking. Until information professionals develop these capabilities, we will remain in the dark ages of data.

This book is for information professionals, especially those who have been thrust into this important work without having a chance to develop these foundational skills. If you're an information professional and have never been trained to think critically and scientifically with data, this book will get you started. Once on this path, you'll be able to help usher in an Information Age worthy of the name.

Stephen Few, a longtime information professional, is best known for his contributions to the field of data visualization. Since founding his consultancy Perceptual Edge in 2003, he has written six books:

• Show Me the Numbers: Designing Tables and Graphs to Enlighten (2nd edition)
• Information Dashboard Design: Displaying Data for At-A-Glance Monitoring (2nd edition)
• Now You See It: Simple Visualization Techniques for Quantitative Analysis
• Signal: Understanding What Matters in a World of Noise
• Big Data, Big Dupe: A Little Book About a Big Bunch of Nonsense
• The Data Loom: Weaving Understanding by Thinking Critically and Scientifically with Data

Above all else, Stephen is a teacher. He believes that deriving value from data to support better decisions and actions is highly skilled work. Helping people develop these skills is his passion.