This article was written by Mark Palmer, host of Executive Programs for Dataiku. Mark is a data and AI industry analyst for Warburg Pincus and a board member for six AI, data management, and data science companies. Time Magazine named him “A Tech Pioneer Who Will Change Your Life.” Mark is a LinkedIn Top Voice in Data Analytics.
Ask a data scientist about their most important skill, and they’ll often list technical chops like Python, SQL, or machine learning. Ask a great data scientist the same question, and they’ll say creativity, curiosity, and intuition — traits are often ascribed to artists, not scientists.
Einstein concurred when he said, “Great scientists are great artists, too.”
Thinking like an artist is a great way to develop your scientific muscle. Here are seven ways data scientists should think like artists and seven exercises to build your creative muscle.
1. Art Aspires to Change Minds
The highest aim of art is to change minds: to challenge the viewer to dream, imagine, or mash old ideas into new ones; to obliterate bias and ignorance; to cut new paths.
Great scientists change minds, too. They go beyond the obvious to find new ideas. They dig deeper. They look wider. When they uncover an unconventional or inconvenient truth, they use data to tell a story, and share it.
To become a better scientist, try this. Reflect on the origins of art you love: a piece of art, a song, a poem, a novel, an essential piece of architecture, or a beautifully designed product. Learn about it for 30 minutes. Take some time to understand the motivation behind it.
Recently, this happened to me by chance. I was wandering around the Museum of Modern Art in New York and saw an exhibit on Charlie Chaplin. I had never thought of him as anything other than a comedian. But I learned that this famous scene from his film “Modern Times” wasn’t “just” a hilarious comedic bit — it was a social commentary. It was a warning about the danger of automation to human society and the human toll on humanity:
As you build the muscle to explore the motivation behind art, try using that skill with data. The next time you spot an outlier in data, wonder why it's there; ponder whether adding new data might make your findings less biased; imagine what message that data point sends about the problem you’re trying to explain.
2. Art Trains You to Look for the Space Between the Notes
Legendary jazz innovator Miles Davis said, "It's not the notes you play; it's the ones you don't play; music lies in the space between the notes." This idea embodies a profound understanding of the importance of space, cadence, and rhythm in composition.
The most important question to ask as you evaluate data is, “Compared to what?” Order, trends, and context matter more than data from a single moment. For example, if you’re evaluating a sales forecast, your job isn’t to report on a number; it’s to explain how it’s changed for better or worse, what changed, and what’s about to change. Your job is to describe the space between the data notes.
Try this. Explore the jazz style of Miles Davis and play Kind of Blue by Davis the next time you’re analyzing information. Listen for the space between the notes in the sound and in your data. Think about order, momentum, space, and movement in what the data says.
3. Art Teaches Creativity Through Forced Constraint
A haiku is a Japanese form of poetry that consists of 17 syllables arranged in three unrhymed lines of five, seven, and five syllables, respectively. That doesn’t give the poet much time to make their point. This art form is an example of forced constraint — deliberately setting boundaries or limitations on resources, time, or methods to encourage innovative thinking.
Carefully selecting words for a haiku is like selecting data insights from a treasure trove of “big data.” The art of extracting ideas from massive datasets forces you to eliminate bloat, unnecessary detail, and what Edward Tufte called chart junk — anything that distracts from your insight.
Try this: Summarize your findings on your next data project in words. Make it as long as you wish. Then, paste your writing into ChatGPT, Bing, or Perplexity (just to name a few!) and prompt it to “Write a haiku based on <your idea.> AI’s attempts are often surprising, revealing, or even funny.
Even better: If you have a friend who likes poetry, ask them to write one. Here’s what my friend Anita Stubenrauch sent me after she read this article:
4. Art Mixes Saltpeter, Sulfur, and Charcoal
As legendary music producer Rick Rubin explained in “The Creative Act,” ancient Chinese alchemists searching for immortality mixed saltpeter, sulfur, and charcoal; they discovered something else: gunpowder. Rubin’s point is that artists mix inspiration from music, art, nature, poetry, novels, and movies to create new things.
Similarly, business innovation can hail from unrelated sources. Henry Ford was inspired by assembly lines for meat packers and applied its tenets to the manufacturing of cars. Airbnb was inspired to improve the experience of staying at a bed-and-breakfast. Slack mixes ideas from email, instant messaging, and file sharing.
Try this: Absorb documentaries, podcasts, and books on the art of business in fields far afield from your own. A few of my favorites are How I Built This, Acquired, and Nuts: The Story of Southwest Airlines. As you explore the data that drives your business, look for similarities that might draw a connection between business ideas you might not have considered before.
5. Art Holds Up a Mirror
Art is often intentionally ambiguous and open to interpretation — it provokes us, stirs emotions, makes us angry, or inspires us. Data can stir us to think, too. It invites us to understand ourselves, things, or tribes of people more deeply. Data reflects our bias, intent, and loyalty.
Data is like art — it presents an idea, and the viewer interprets it.
Try this: Find a friend who loves a piece of art, song, or movie you love. Ask how it makes them feel and notice how they may see different things in the same thing. Notice what the mirror shows to them.
Then, keep this idea in mind as you present your data findings. For example, a suddenly increasing pipeline might look good to you. At the same time, an experienced salesperson might notice a quarterly miss preceded the increase — a sign that slipped deals have artificially enlarged the current pipeline.
6. Art Teaches How to Use Negative Space
In photography, the negative space of an image is everything other than the subject: the foreground, the background, and the visual “breathing room” of a scene. For example, the dogsled in the lower right corner of this gorgeous backdrop of snow and sky makes you wonder: Who are these people? Where are they going? Where did they come from? What’s their mission? How cold is it? Are they tired?
Negative space invites the viewer to think, which is why it’s one of photography's most essential composition techniques.
Great breakthroughs in science come from exploring negative space — noticing what’s missing and being curious about the “rest of the story.” One data point sparks the curiosity to look for others.
Try this on your next project: Pick one small, surprising piece of data, put it in the “lower right-hand corner” of your curiosity, and explore the negative, unexplained, open space. Fill in the picture. If the forecast is bad, wonder why. Try searching for correlations between that forecast number and the number of leads generated six months prior, or search for environmental factors that might explain the drop, like weather, interest rates, or customer sentiment.
7. Artists Journal, Sketch, and Play to Unleash Creativity
One of my favorite books about the most creative, ground-breaking artists and scientists is a boring-sounding book called “Daily Rituals: How Artists Work.” It explores the daily habits of 150 legends, from Igor Stravinsky to Ben Franklin to Jane Austin and Ann Rice. It explains their daily routines: When they woke up, where they worked, when they worked, spanning hundreds of years.
One thing almost all of these great thinkers and creators do is keep a personal journal. With nothing more than paper and pen, they sketch, reflect, replay, remix, and play with ideas.
Modern research shows that the more time we spend formulating questions, the more creative and original our work becomes. The masters of art and science didn’t need the research; they know and knew this. So Grab one of Mason Currey’s books and check out their habits. I love to collect images from their journals. Here are entries from Frida, Da Vinci, Galileo, Jonny Ive, my instructors from Stanford d.school (their School of Design), and author Tim Ferriss, all of which espouse the benefits of using a journal to externalize ideas from your head.
Data scientist William Palmer explains that data scientists should keep a journal, too. He uses his journal to “Reflect on findings, keep best practices at my fingertips, maintain a record of problems I faced and how I resolved them.”
Not sure how to journal effectively? Watch Tim Ferriss’ video How I Journal and Take Notes | Brainstorming + Focusing + Reducing Anxiety, which has almost one million views. I watched it four years ago, which changed how I keep my journal. Try it for 30 days; every morning, take 10 minutes to review yesterday and think about today.
Great Artists Are Brave
In “The Practice,” Seth Godin explains that great artists are brave. The act of asking “Why,” searching for inconvenient answers, and sharing them is uncomfortable. Author Kate Chopin agreed over 100 years ago, “The artist must possess a courageous soul that dares and defies.”
So be brave — go forth and be artsy! Go to a museum. Read some poetry. Doodle in your journal. Play some music that soars or swings. Building your artistic muscle might inspire you to do great data science. To spot what’s missing. To inspire others. To dare to defy conventional thinking. To point out negative space. To acknowledge what the data mirror shows as you hold it up to yourself and others.
Just like great art.