“Data Science” is obviously a trendy term making it way through the hype cycle. Either nobody is good enough to be a data scientist (unicorns) or everybody is too good to be a data scientist (or the truth is somewhere in the middle).
Gartner hype cycle (Wikipedia).
It has always been the case that advances in data engineering (such as punch cards, or data centers) make analysis practical at new scales (though I still suspect Map/Reduce was a plot designed to trick engineers into being excited about ETL and report generation).
Data Science 1832: Semen Korsakov card.
However, in the 1940s and 1950s the field was called “operations research” (even when performed by statisticians). When you read John F. Magee, (2002) “Operations Research at Arthur D. Little, Inc.: The Early Years”, Operations Research 50(1):149-153 http://dx.doi.org/10.1287/opre.126.96.36.19996 you really come away with the impression you are reading about a study of online advertising performed in the 1940s (okay mail advertising, but mail was “the email of its time”).
In this spirit next week we will write about the sequential analysis solution for A/B-testing, invented in the 1940s by one of the greats of statistics and operations research: Abraham Wald (whom we have written about before).