Under most circumstances, there was no "big data" in the first place, and many businesses discovered that you can't magically derive insight, create value, buil

Under most circumstances, there was no "big data" in the first place, and many businesses discovered that you can't magically derive insight, create value, build features, solve problems, etc. by performing aggregation and data science on most forms of data, especially if that data is not "big." No one can even define what "big" means. How many "rows" of data do you need for it to be "big"? How many "columns" per record? How many relationships both implicit and explicit? How fast does that data change or grow? How structured or unstructured? It's entirely a value judgment that many engineers and managers had no business determining as being "big." The true "big data" became so ubiquitous and accessible that there became no reason for anyone to care about it outside the bubble of Silicon Valley. It's just data, and really was all along.