If only my non-statistical peers would recognize that sampled=fast and fast=more checks and explorations. It's like they recognize that fast compile times are a great thing (I've had to wait in line with punchcards, and it sucks), but they are completely oblivious to the exact same argument when it comes to data.

Why spend years learning those results when you can ignore them at no cost?

And have a happy client that finally gets the results he wanted when the other analysts said it was impossible.

Elsewhere he talks about how subsamples are chosen because they take but seconds to run instead of minutes. If a sample is small enough that you're saving that much time, and analysis is that cheap, you can still do five-fold or ten-fold cross validation in less time than the full data set analysis and get a very good idea on if your subsample is representative of the data or not.