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.
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About the Author
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.
Table of Contents
Chapter 1 Construct A Loom 1
Data sense making
The ability to weave data into understanding
Requires a spectrum of skills. Critical thinking and scientific thinking are foremost among them.
Chapter 2 Think Critically 13
When we think critically, we apply logic and avoid cognitive biases.
Chapter 3 Think Scientifically 47
When we think scientifically, we apply the scientific method.
Chapter 4 Question The Data 67
Thinking critically and scientifically leads us to ask essential questions about data to improve the reliability of our findings.
Chapter 5 Measure Wisely 83
Metrics can be powerful, but we often measure the wrong things, measure the right things ineffectively, and use measurements in harmful ways.
Chapter 6 Develop Good Thinking Habits 103
In addition to critical thinking and scientific thinking, data sensemaking is also enriched by developing good thinking habits.
Chapter 7 Develop A Data
Sensemaking Culture 111
Effective data sensemaking is undermined by most organizational cultures. We must promote the cultural changes that are needed to embrace critical and scientific thinking with data.
Epilogue: Embrace The Opportunity 121