When coming up with a solution to a problem, I find it useful to picture what success looks like. This helps me develop strategies to get to the end goal. (Here, we’re assuming that we already know what the problem is. But don’t underestimate how hard it can be for you and your team to identify a problem.)
In this post, I want to set out some guidelines on developing and carrying out effective and sustainable data science projects. I came up with this guide after making several mistakes in my own projects and seeing others make their own.