Successful ML and Data Engineering projects aren't successful just because ML and AI are the latest buzz words. They are successful because of the data scientists ability to look, see, imagine and show complex relationships hidden in the data sets.
For years, I noticed coworkers talking in circles trying to convey abstract concepts in meetings. I found it so frustrating that I sought to find a better way to communicate ideas so I wouldn’t add to the confusion. This lead me to Dan Roam’s books
My Visual Thinking Playbook is built on Dan Roam's four-step process that helps turn ideas into clear, impactful visuals:
1. Look – Collect raw visual information.
2. See – Identify meaningful patterns in what you observe.
3. Imagine – Fill in the gaps and connect ideas.
4. Show – Communicate ideas visually for clarity and impact.
"Visual thinking isn’t just about drawing—it’s about structuring information in a way that our brains naturally process. Whether through diagrams, maps, or sketches, this process helps turn messy ideas into clear insights."
Step 1: Look – Collect and Screen Information
Step 2: See – Identify Meaningful Patterns
Step 3: Imagine – Make Invisible Patterns Visible
Step 4: Show – Make Ideas Clear with Visual Frameworks
"The real power of visual thinking isn’t just in seeing what’s there—it’s in imagining what’s missing and filling in the blanks."
"Visual Thinking means taking advantage of our innate ability to see - both with our eyes and with our mind's eye." —Dan Roam
"Visual thinking is not about making things look pretty—it’s about making them clear. A rough sketch that communicates an idea is more valuable than a polished diagram that confuses people."