I think you can say the same about most professions that are "big picture" ("individual picture" professions meaning teachers, doctors, EMS; folks that help individuals rather than larger trends).
The reason here is similar to why science oftentimes appears fundamentally worthless - most of the time you uncover absolutely nothing of importance. I think the same is true for data organizations. When you're looking for large patterns in the data you're going to strike out a lot. And that's not on an individual level, but on an org level - a lot of teams within the broader data organization will never produce anything of value. But at least they'll try.
With respect to data quality - fix it then! That seems like an immediate way to make your work less "fundamentally worthless". I understand that fixing data quality is hard (I spent >12 months working on that problem at my current company), but it is not a worthless endeavor.
Depends massively on the company! I am indeed one of the nerds that goes to bat for fixing data quality issues, but it takes long enough that I frequently look at these projects and think:
"It might take the majority of my working life to help this one company migrate this terrible enterprise system to a much better enterprise system. All my time will be spent in meetings, and educating hostile people who just want to do the work faster. Is that something I'd be proud of at the end of my career?"
And the answer is, to some degree! But I think we'd all like to work with people who get it or our friends, and if we're not there yet, it's really a question of whether we're at a position in our lives where we can search or prioritize other life improvements.
The reason here is similar to why science oftentimes appears fundamentally worthless - most of the time you uncover absolutely nothing of importance. I think the same is true for data organizations. When you're looking for large patterns in the data you're going to strike out a lot. And that's not on an individual level, but on an org level - a lot of teams within the broader data organization will never produce anything of value. But at least they'll try.
With respect to data quality - fix it then! That seems like an immediate way to make your work less "fundamentally worthless". I understand that fixing data quality is hard (I spent >12 months working on that problem at my current company), but it is not a worthless endeavor.