Yes, there are of course other topics that are not just "tooling" related. But data science does have a tooling problem. Lots of unsolved tooling problems, in f

Yes, there are of course other topics that are not just "tooling" related. But data science does have a tooling problem. Lots of unsolved tooling problems, in fact. Especially when you're dealing with larger data science orgs, you start running into a lot of inefficiencies and problems that do need to be solved in a more systematic way. Making data scientists more efficient allows them to actually work on the more interesting problems and ask the questions that deliver value.