For an actual in-depth look at the origin and deep history of data science and statistics, check out the book the "The 7 Pillars of Statistical Wisdom"[1]. It recounts historical anecdotes such as the Trial of Pyx[2] at the London mint (an early example of random sampling, how the "foot" was defined by literally having a bunch of guys put their feet end-to-end, how least squares was applied to orbits by Gauss, how in the 1940's inverting a 14x14 matrix (for Leontief's input-output analysis in economics[4]) was a big data problem, and so on.

I personally believe data science began with Bacon's Novum Organum[5], which describes an inductive method[6] starting from tables of facts and simplifying them until you reason general truths that may be treated as axioms for the purposes of deductive reasoning. This is no different in principle then the model fitting and prediction we do today.

I personally believe data science began with Bacon's Novum Organum[5], which describes an inductive method[6] starting from tables of facts and simplifying them until you reason general truths that may be treated as axioms for the purposes of deductive reasoning. This is no different in principle then the model fitting and prediction we do today.

[1]: https://www.amazon.com/Seven-Pillars-Statistical-Wisdom/dp/0...

[2]: https://en.wikipedia.org/wiki/Trial_of_the_Pyx

[3]: https://www2.stetson.edu/~efriedma/periodictable/html/Ga.htm...

[4]: https://www.math.ksu.edu/~gerald/leontief.pdf

[5]: https://en.wikipedia.org/wiki/Novum_Organum

[6]: https://en.wikipedia.org/wiki/Baconian_method