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  • Oscar Martinez (Valerock)

A dashboard by Van Gogh.

Updated: Aug 26

What would a dashboard by Van Gogh look like? Would Rembrandt create a detailed and colorful data visualization? Or would Picasso use abstract shapes to represent trends in customer behavior? Let's for a minute imagine that Van Gogh, Frida Kahlo Da Vinci, or Mondrian, with their esthetic genius, were data analysts or business intelligence developers in the 21st century, how would their dashboards look like?

In this blog post, with the support of AI project Midjourney, we'll explore how some of the most famous painters in history might approach business intelligence and analytics.

Starting with Van Gogh; his paintings are full of intense colors and emotion. As a data analyst, he would likely use his dashboard to communicate the passion and intensity that he feels about his work. His dashboard would be a colorful explosion of information, with bold visuals that demand attention.

Leonardo da Vinci, his drawing style was very precise and his data analysis would likely be very accurate. He was the archetype of the renaissance painter, with a focus on realism and capturing the essence of his subjects. His data dashboard would likely be a collection of meticulously drawn charts and graphs, with clear and concise information.


Next, we have Rembrandt. His painting style was very dramatic and emotional, often using light and shadow to create a sense of depth and mood. As a data analyst, he would likely focus on presenting trends in an engaging way that would capture the viewer's attention. His data dashboard might include dynamic visualizations that shift and change as new data is added.


Frida Kahlo, her paintings were deeply personal and often reflected her own life experiences. As a data analyst, she would focus on telling stories with her data. Her data dashboard would be a collection of narratives that help explain what the numbers mean to everyday people.


Moving on, we have Picasso. His paintings were often abstract and non-representational. As a business intelligence consultant, he would likely use unusual shapes and colors to represent complex trends in customer behavior or spending patterns. His data dashboard would be an eye-catching masterpiece that stands out from the rest.


Then, we have Goya. His paintings were dark and often eerie, with a sense of foreboding. As a data analyst, he would likely focus on identifying potential risks and warning signs in the data. His dashboard would be full of dark colors and sharp angles, with warning messages front and center.


I would love to have seen Gustav Klimt's data analytics creations . His paintings are full of ornate patterns and gold leaf. As a data analyst, he would likely use creative visuals to communicate information in an elegant way. His dashboard would be a work of art, with beautiful visuals that tell a story.


Hundertwasser dashboards would have been really funky! His paintings are full of bright colors and organic shapes. As a data analyst, he would likely use unconventional visuals to represent data in a fun and interesting way. His dashboard would be a colorful explosion of information that is both visually stimulating and informative.


Mondrian would be all about the basics. His paintings are composed of simple geometric shapes in primary colors. As a data analyst, he would likely use basic charts and lots of treemaps and graphs to communicate information clearly and concisely. His dashboard would be clean and orderly, with a focus on simplicity.


Finally, we have Yayoi Kusama, her dashboards would be really fun, and probably a little bit psychedelic. Her paintings often feature repetitive patterns and bright colors. As a data analyst, she would likely use creative visuals to communicate information in an engaging way. Her dashboard would be full of fun colors and patterns, with a focus on engagement, very handy for clustering analysis.


In conclusion, each of these painters would likely create a very different analytics dashboard, based on their styles and approach to painting. However, all of them would be focused on creating an appealing and informative dashboard that tells a story with the data. We, as data analysts can find inspiration in this type of exercise to better understand how to communicate information in an engaging way. Thank you for reading!

Did you enjoy this post? Let us know in the comments below! And if you want to learn more about data analytics, check out our other blog posts or sign up for our mailing list.


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