Last month I gave a talk at csv,conf on "Getting Credit for Invisible Work". The (amazing) csv,conf organizers just published a recording of the talk. (slides here). Give it a watch! It's only 20m long (including the Q&A).
Invisible work is a concept I've been trying to pin down for a while. I've found that a lot of the hard important work that goes into producing good data analysis is invisible. Nobody ever sees the hypotheses we discard when doing EDA. Nobody ever sees the problems we avoid with our intuition.
We explore complex data, so we can distill our findings into a simple narrative. If we’re doing it right, we make our work look simple. This is super valuable, but can cause problems when we try to demonstrate our value. This talk covers some strategies for getting credit for this super valuable but invisible work.
I'd love to hear your thoughts! Shoot me an email!