"Janitor Work" is an "it depends" situation. I agree with the article that data wrangling is counter-productive, where the 80/20 ratio for wrangling/analysis ca

"Janitor Work" is an "it depends" situation. I agree with the article that data wrangling is counter-productive, where the 80/20 ratio for wrangling/analysis can still be improved. But I disagree with the notion that doing such work never leads to a data scientist's technical growth. Such dirty work allows data scientists to be more effective because they can take data of any form, know its shortcomings, and generate insights from it with proper scope. Those who would want to rely on 'clean' data always handed down to them, I must say, are spoiled. On a side note, it's narcissistic and cocky to use the word "janitor" for such an issue. It's not like data scientists should only be worthy of doing the illustrious part of the job and never the dirty tasks, right? I'd still go and take the broom and clean up the mess when no one else can.