Introduce yourself and describe your work:
I teach people how to tell a story with their data. I started out by blogging about data visualization (that’s the formal name for my field) and was one of the very first voices on the scene. I’ve since written 3 books and now I travel all over the world teaching people my methods.
What do you consider to be your most important career achievement or discovery?:
I invented methods for creating graphs that are perfect for certain data stories. That’s cool. But the biggest outcome is when organizations change the way they think and act because of better data visualization. When clients tell me victories of effective decision-making, I dance in my office.
During times of imposter syndrome or feelings of discouragement, what or who helped you persevere?:
I keep a folder in my inbox called Sweet Emails from Fans. When I feel discouraged, I read through that collection. Knowing that I changed one person’s life for the better helps me get out of whatever death spiral I’m in and stay focused on why I do this work.
How does your work impact people and the world around us?:
When we can read charts better, we can all make better decisions about our lives. From the rings on your Apple Watch to the COVID dashboards we were looking at so frequently, data is everywhere. Bad data graphs lose people. Good visuals engages, inspires, and creates change.
What is a unique fact about your career/industry?:
This field is so young, I’m one of the OGs and I’m only in my 40s. When I was a kid, this career wasn’t even a twinkle in an eye on career day. This is a testament to how fast the world evolves and how we can craft a path forward even if we can’t see the destination yet.
What trends do you see in your industry?:
The data visualization world has started focusing more on accessibility – that is, making sure our work can be viewed by people with various disabilities (and some folks are even working on data sonification, for those who can’t view!). We’re just now starting to expand that focus to inclusivity more broadly. For example, I’ve started highlighting how qualitative data visualization can be done to effectively include more voices. And I’ve been emphasizing the many ways data has traditionally been visualized in some indigenous communities – long before the typically-told history that it emerged from white men in Europe.
What advice do you have for other women or nonbinary individuals considering this field?:
As young as this field is, it’s still very much an old boys club. Connect with the people who share your values and support each other. The demand for data visualization is strong and growing – we need you. We need you to be you.