Welcome to amoredatus

2026-01-25
personaldata scienceintroduction

If you've found your way here, welcome. I'm Jordan, and this is amoredatus — a passion project born out of my Master's studies in Data Science.

The name comes from the Latin amore (love) and datus (given, or data). It's a bit of wordplay, but it captures something real: I genuinely love working with data. Not just the technical side — though there's satisfaction in a clean pipeline or a well-tuned model — but the moment when numbers start telling a story. When patterns emerge from chaos. When data actually changes how someone thinks about a problem.

Why this site exists

During my Master's program, I found myself constantly exploring datasets that had nothing to do with my coursework. Edmonton's snow clearing complaints. Property tax trends. Public transit patterns. I'd start with a simple question, and hours later I'd be deep in analysis, building visualizations, trying to understand what the data was really saying.

I realized I wanted a place to share that work. Not buried in a GitHub repo or a PDF assignment, but somewhere accessible — where the analysis could breathe and maybe spark a conversation.

That's what amoredatus is for. A space to tell data stories. To share what I'm learning. To document the messy, iterative process of turning raw data into meaningful insight.

What you'll find here

I plan to share a mix of content:

  • Data stories — Deep dives into interesting datasets, with interactive visualizations and narrative analysis. My first project explores Edmonton's snow clearing crisis using 11 years of 311 complaint data.
  • Technical insights — Lessons learned from building pipelines, working with people analytics platforms, and navigating the ever-expanding landscape of data tools.
  • Reflections — Thoughts on the craft of data science, the ethics of analytics, and what it means to do this work well.

I'm particularly interested in people analytics — the intersection of data science and human behavior in organizations. It's a field where good analysis can genuinely improve how people experience work, and bad analysis can cause real harm. That tension keeps me sharp.

An invitation

I don't see this as a broadcast. I'd love for amoredatus to be a place for conversation and collaboration. If you're working on something interesting, have feedback on my analysis, or just want to connect — reach out. The best insights I've had have come from conversations with other people who care about this stuff.

Data science can feel isolating sometimes. You're heads-down in code, wrestling with messy datasets, trying to figure out why your model isn't converging. But it doesn't have to be. There's a community of people out there doing this work, asking hard questions, and pushing each other to be better.

I hope amoredatus can be a small part of that.

Thanks for being here. Let's see where this goes.

— Jordan