I'm dealing with everything from very deliberate logging, people who just dump class names with arguments, people who thought it was a good idea to log the localized version of the feature, and people who log in hex.
I would laugh; but I just feel bad. I remember my boss telling me 80% of your job is going through a given data set and cleaning it so it becomes usable more so than anything. One of the mandatory things I built into some of the Obama campaign's models years ago was the idea that your data had to be clean, because I'm freaking lazy and don't want to clean that shit. Also, super complicated models as well as cleaning algorithms just get the "glassy eyed" look from superiors, who then proceed to often ignore it.
It's actually why I do sports analytics stuff for fun on the side - SportsVU / etc data sets are SO MUCH CLEANER HOLY CRAP. Though, to be fair, helping out on an update of DVOA was definitely a fun step, as was working with PFF.
NFL is my favorite sport for analytics, in that it's a much more complicated interconnected system, so much more systems engineering and multivariable regressions to play with. MLB almost feels like it's figured out except for the qualitative clubhouse aspects (which I think you might actually be able to get if you figure out a RPM type measure); and NBA has so many awesome folks already that it's just fun to watch them.
That said; I do need to restart some of the DOTA 2 and Street Fighter projects I have sitting on my computer.
My job is all technically BI - but it's more of "combine your aerospace knowledge and your analytics and tell us what's wrong with this, show the numbers, and then tell us how to fix it from an engineering point of view as well as a mathematical point of view."