I totally get your skepticism but the bottom line is that throwing computing power at a problem generally leads to a much better solution even if only because you can do a much more extensive grid-search. This doesn’t have to be using some complex cluster like you could just have n copies of the same VM that each run experiments with parameters pulled from a Google sheet until all the experiments are done.

Sure, the cloud providers sell computing power but it’s a race to the bottom and makes much more sense than buying hardware for these kinds of bursty analytics workloads.

I don’t think “Big data” from a stats perspective is analogous to census data - in some cases yes but for applications like recommendation engines you lose a lot of valuable signal by sampling.