When we first started Data Chefs, we thought we were going to focus on making it a lot easier to clean up and slice & dice data. Many folks in “data science” will tell you that they spend the vast majority of their time prepping their data before they can analyze it, so if we could make this easier for folks in the community, it would be a real win.
After banging our heads against various doors, we realized we were trapped the chicken or the egg problem: without concrete to show folks, the idea that they could have any say on how easy/hard the tools for wrangling data were seemed overwhelming, and without community folks to figure out what “easier” looked like, we wouldn’t be able to convince data geeks to build easier-to-use tools.
So over the past six months, we’ve gradually been shifting our focus. You’re going to start seeing a lot more about data visualization on this blog. That’s because even if people are scared of or overwhelmed by the idea that they could shape the tools they use, everybody likes shiny objects. So going forward, we’re going to explore what it means to make an organization data visualization-literate, and we’re going to do some D3 experiments to see if we can smooth its learning curve.
That said, we aren’t entirely giving up on data manipulation. Although we weren’t able to put together a community of folks, we did learn a lot about the problems that a Data Chefs approach would have to solve; I’ll blog about it in the next few months.