Three Questions with… Guillermina Sutter Schneider

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Guillermina Sutter Schneider is a product specialist at Datawrapper. She likes coding, color theory, numbers, and Berlin, not necessarily in that order. You can find out more at sutterschneider.com, or connect with her on Twitter @gsutters

1. What’s one topic you would love to visualize but have never had the chance to?

My immigration adventure. Over the past two years, I haven’t lived in the same country and city for more than six months. Because my Green Card process for U.S. permanent residency was delayed due to Covid-19 (the government shut down for a few months and my paperwork took longer to process), and because I then decided to change career paths and had to apply for a German Blue Card residence permit, I ended up moving a lot and living in the United States, Curaçao (a beautiful Dutch island in the Caribbean), Argentina, and Germany over the course of those two years. I worked remotely while visiting friends and family, made new friends, learned a new language (Dutch), and got to know myself better. This is something that I have been wanting to visualize for a while now, although I haven’t had enough time to brainstorm and think about what exactly I would like to visualize and how. 

2. If you had to choose an entirely new career path, realistic or not, what would it be?

When I was 17 years old and had to pick a college major, I made a list of all the potential career paths that interested me. Audio/sound engineering, petroleum engineering, violoncello, philosophy, and international affairs were on that list. I ended up getting a degree in economics and later on in data science. Although I very much enjoyed what I studied, I would change careers to aerospace engineer because I am a big fan of Elon Musk and would love to travel to space one day.

3. If you could be any type of chart, what would you be?

I would be a sparkline. I like sparklines because they are versatile tiny charts and minimalistic. They can be accompanied by numbers, words, high and low values, average lines, etc., or just be presented on their own to show the overall evolution of some variable. In Beautiful Evidence, Tufte described sparklines as “a small intense, simple, word-sized graphic with typographic resolution.” You have probably seen sparklines on your Twitter account stats or your Stocks app on your iPhone. If you have, you may have noticed how they easily fit into so many different contexts without compromising the data-ink ratio. This is why I like sparklines.

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