The course brought four of us together as a team Jakub Kašpar, Martina Hromádková, Matyáš Bureš, and me with one shared dataset and four different angles on it. We worked from Most Streamed Spotify Songs 2023 and the target audience for the final infographic was simple: people who listen to popular music. Purpose, equally simple: entertainment, pop culture overview, not policy.

My slice of the dataset was tempo. Specifically BPM. I wanted to know whether listeners in 2023 leaned toward slow or fast songs. The first decision was definitional. What counts as slow? What counts as fast? Once I'd drawn those lines, the data was clear. Fast songs win.

Once I had that result, I wanted to push further. Instead of two categories I split tempo into more granular bands and filtered the dataset by each one. I used AI to help with the filtering, which was efficient until it wasn't. The model regularly produced confident answers that turned out to be wrong on second look. I ended up validating every step manually, which is a lesson I keep relearning. AI accelerates the work, it doesn't replace the checking.

The harder part of the project wasn't the analysis. It was the visualisation. I went through several versions of the chart and none of them quite landed. The data was clean, the result was clear, and the visual still ended up reading as cluttered or confusing depending on which version you looked at. That gap between knowing what the data says and showing what the data says is something this course made me actually take seriously.

There was one finding I didn't see coming. Among all the fast-tempo, high-energy songs in the dataset, Taylor Swift came out on top. Again. She's apparently genre-proof and tempo-proof. As a DJ, I left the project with one practical thought: this kind of dataset would be genuinely useful for building a set, not just for an infographic.

The course taught me that data work is two crafts, not one. Finding what the data says is half. Showing it so someone else can see it without explanation is the other half. I got better at the first. The second is still on the to-do list.