As a budding data practitioner with serious attention and focus issues, it’s been difficult to discern a path through the data landscape. It was a miracle I landed on this field as an interest in the first place, having toyed with the idea of going into cybersecurity (at one time!) and completed a master’s degree that focused on culturally sensitive UI/UX design that wobbled between theory and practice. Now, walking down the data path, I’m at the nexus of seemingly dozens of possibilities, many overlapping, but widely different in terms of required start up skills. (And a search through the archives shows I’ve written a version of this post before, go figure.)
A lifelong amateur artist, I naturally gravitated to the field of data visualization. But beyond illustrating the data is telling the story behind it. Then, there is the accessibility and UX of data visualization. From there, you have the techniques of data management and distribution to stakeholders. I’m not even going to touch the advanced data science arms of predictive modeling and analytics and big data management, not yet. Underpinning all of these is data ethics and what it means to collect, use, and represent data. Needless to say, I’m drowning in a sea of books and Udemy courses that I usually end up ignoring after long days of work that don’t always have much to do with the practice of data.
That isn’t to imply that I don’t have experience in a lot of the above; the problem is that I have a little experience in most of it and can’t figure out how to move forward most efficiently. My interests and work duties change on a weekly basis, and things like SQL and stats aren’t the easiest thing to refresh & maintain outside of a daily use case. Like languages, you use it or you lose it (at least, my brain does).
So now what? Party, I’m writing this to mark my path as my brain flits between branches and I get a better idea of what’s out there in the data landscape. From here I can sketch where to go next: what courses to complete, what books to read, what languages, libraries, and software to practice or pick up. I think what would probably be most helpful is a resource collection and learning plan tagged with sub-fields (as I understand them) and estimated time requirements. This will also be a good exercise in reviewing all the things I’ve bookmarked in various browsers and apps. When I build it out I’ll share it here in case it’s ever useful to anybody else.
So there are my data musings for this week and an actionable goal to work on over the weekend. Here’s to walking a bit further down the path!
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