The most common DSA prep mistake I see at the FAANG band isn't undertraining or overtraining. It's training as if Amazon, Google, and Meta all sample from the same pattern bag. They don't. After mapping company tags across 450+ handpicked interview problems, the gap between Amazon's pattern footprint and Google's is larger than most candidates expect, and materially changes how prep time should be allocated. TL;DR: Amazon spans 11+ distinct DSA pattern families, the broadest of any major company. Google has narrower coverage but a distinctive emphasis on predicate search (binary search on the answer space, not on a sorted array). Seven patterns appear at six or more companies and form the universal baseline that every FAANG candidate has to own before specialising. The seven patterns every FAANG round assumes you can run Before company specific differences matter, there's a universal baseline. Seven patterns appear at six or more major companies in the data set.…