This week is my last week working at The Arts Partnership.
I’m both sad and excited to announce that I’m leaving The Arts Partnership and have accepted a position as a data analyst.
If you’re confused about that career transition, I understand. Typically, the career step after arts administration isn’t going on to being a number cruncher.
By being immersed in both worlds, I’ve noticed that my background in the arts plays a vital role in my upcoming career.
On the first day of one of my classes in the Master of Science in Business Analytics program at NDSU, our professor asked us if data analytics and visualization is more of an art or science.
It’s a hard question to answer, but here are 5 skills I’ve learned from my practice as an artist and from working in the arts that will directly serve me in my new role, as well as some photos from my time at TAP.
The most striking skill that exists in both the arts and data analytics is the importance of storytelling. Just about every artistic medium — theatre, music, visual arts, literature, film etc. — has storytelling at their core. I spent four and a half years studying music as a vocalist. There are technical skills you must master in order to become a better musician, but it’s the story you are able to tell with the music that will communicate the meaning and emotion behind it all.
One of the books that has been influential in my journey into data analytics is Storytelling with Data by Cole Nussbaumer Knafflic. This book conveys a similar theme: that numbers and data are vital, but it’s the story you tell about them that allow you to draw the greatest insights and make important decisions. (I talked more about this in a blog post two years ago reflecting on the North Dakota Council on the Arts State Convening.)
I do not claim to be a visual artist. I think that much can be concluded from when we drew eyes with Jescia Hopper on TAPpy Hour.
That doesn’t mean I’m totally inept, though, and the fact that I do have at least a little bit of visual aptitude has been incredibly useful in data visualization.
In one of my classes on data visualization, we got a crash course in color theory and design principles on the second day. We broke down the differences between hue, saturation, and lightness. The color wheel showed up on our slides in multiple different places and talked about how people interpret the meanings of colors. Along with color, we would talk about Gestalt Principles of visual perception and how we could use visual techniques to lead people on how to interpret charts and graphs.
While you’d be hard-pressed to find charts and graphs in a gallery exhibition, aesthetic choices are an important component of communicating data.
About a year ago I had an overly dramatic realization: music theory and data analytics are incredibly similar. This section is going to be a little bit dense on music theory, and if you don’t understand or care: that’s okay.
I loved the music theory courses I took in undergrad. I loved sitting with an 8-page art song and figuring out what those little black dots on the page were doing in the context of the song. It involved looking at the notes themselves, figuring out the D an F# and an A make up a D Major chord, but also looking at the context of what that D Major chord is doing in the piece, and figuring out that it’s actually functioning as a secondary dominant rather than a II chord AND that the secondary dominant paired with the line of text about clouds meant the singer was actually talking the pain of unrequited love.
That may be an extremely specific example, but to put it simply, I found out what those three notes and the lyrics that went with meant in context.
Those skills are directly transferable to analytics. You can know that adding up all of the numbers and dividing by the count of the numbers will give you the average, the same way a D, F# and A make up a D Major chord, but it’s important to know what the average means in context.
A lot of art songs and choral pieces are in languages other than English. It’s a vocalist’s job to make sure that even if the audience doesn’t understand the language you are singing in, they can still understand the meaning behind it.
To many, data and numbers are like another language. It’s important to be able to communicate their meanings to members of your audience who don’t speak that language.
The arts are a uniquely human sector; everything we do is somehow conveying the human experience.
By playing a character in a play, you are transforming yourself into someone else. By singing an aria, you are telling someone else’s story. By reading a poem, you are getting a glimpse into the mind of another human being. For me, listening to and performing music allows me to feel emotions that I have never experienced before.
Every job, every role, every person benefits from empathy. Empathy for your coworkers, empathy for the people you’re serving, empathy for everyone. While I’m nowhere near a perfectly empathetic human being, I believe being in the arts for so long has trained me to approach issues with humanity and empathy.
This week and next will involve a lot of transition for me, so I thought it would be the perfect opportunity to look back on my years at The Arts Partnership using charts and graphs.
I started at TAP in January of 2018. It’s hard to quantify my 3+ years, but that’s never stopped me from trying before! This is my attempt to break down the work I did into the language of my upcoming career — numbers.