Searching for Answers in Data

When I took my first tech job, almost three years ago in August, my soon-to-be-manager asked me during the interview which direction I wanted to head in my career. Right that moment, I wanted to be heading anywhere that didn’t involve collecting grocery carts in front of a Walmart, but I didn’t say that.

I had given thought to my dream jobs, after all, and I told him I had a view towards doing interaction design, especially with language but also visual.  I had—and retain!—a lot of interest in how we use computer interfaces. I wanted to make things usable, understandable, and accessible across a wide base of users. I saw interaction design as a marriage of creativity and science.

Instead, I got thrown into the deep end of a different pool altogether. I became a back-end engineer on a team that handles massive amounts of data, and I floundered a bit before learning to swim. My position led me into solving mysteries instead of designing interfaces. More specifically, I got tasked with figuring out how things work and at the same time fixing bugs or finding data anomalies. I took to this slowly, I remember, needing a lot of guidance before getting the hang of it.

But it actually got pretty interesting to me. I was watching a lot of Law & Order: SVU at the time, and I felt like Olivia slowly stitching together a crime as the clues unraveled. I learned really important skills about how to drill down to troubling artifacts in large amounts of data, form a solid problem statement, and then figure out the next question to ask (and answer), and so on, until I knew everything I needed to know.

It was always really satisfying to figure out who (or what) did it, to gain an understanding how simple rules interacted to form complex emergent phenomena. Having worked at data manipulation in various ways for a few years, I’m beginning to appreciate finding answers in data, and I’ve started realizing I’d rather learn more about plumbing data for knowledge.

I’m not exactly sure where to begin at this point, but I know I want to lead my professional life towards data analysis in general and maybe visualization or even interaction in particular. I’ve realized that the human brain can do things that computers still cannot, especially when it comes to understanding trends, changes, things in motion, and imprecisions. Data visualization and interaction is the perfect place to allow our brains to make sense of complex systems in ways even computers cannot yet.

So, where do I start? For now, I’m going to pick up R or D3 and see where they lead me.