This story has become the stuff of urban legend and puts entirely too much onto John Tukey (who deserves a great deal of credit in other areas). It's become so common in some circles that people who buy into this story will stop talking to you or at least ignore that this story, which makes big circles in stats and ML circles and is entirely wrong.
Peter Naur coined the term in the 60s as an alternative for "Computer Science" but with a focus on the processing of Data vs abstract computation.
In the stats world, Chikio Hayashi proposed the same term in the 90s and it was followed by Jeff Wu a year later and outlines more or less the broad strokes of modern data science and saw it emerging as a new discipline from stats, but not necessarily as a computationally based discipline like CS.
Tukey argued for something a bit broader, "data analysis", as a more focused discipline -- but as a separate thread from Naur's data science. Data has been analyzed for centuries anyways -- Tukey's main contribution was to bring several data analytic disciplines together under one-term, but his vision wasn't for data science, it was for data analytics which is, depending on who you ask, either a different discipline or an umbrella so large that it includes data science among others.
I'm old enough to also remember data processing turning into data analysis, expert systems, data mining and so on. Statisticians were off working on chalkboards and hand-fitting fitting curves with calculators during all of this. Once the stats folks started realizing, sometime in the 2000s, the Computer Science had made better and more predictive tools and was a better approach for many observable phenomenon, statisticians the world over bundled up all the different disciplines they could claw together in a black hole and shot at these other disciplines, then wrapped it all in the incomprehensible statistics jargon and claimed it as their own shouting Tukey's name to the mountains.
It's not really worth fighting at this point, but this history is revisionist urban legend at best.
Source: I've worked in data disciplines since the 90s and remember when all the roles I used to work in that dated back decades, suddenly required PhDs in statistics as Stats majors flooded the market in the 2000s.
Peter Naur coined the term in the 60s as an alternative for "Computer Science" but with a focus on the processing of Data vs abstract computation.
In the stats world, Chikio Hayashi proposed the same term in the 90s and it was followed by Jeff Wu a year later and outlines more or less the broad strokes of modern data science and saw it emerging as a new discipline from stats, but not necessarily as a computationally based discipline like CS.
Tukey argued for something a bit broader, "data analysis", as a more focused discipline -- but as a separate thread from Naur's data science. Data has been analyzed for centuries anyways -- Tukey's main contribution was to bring several data analytic disciplines together under one-term, but his vision wasn't for data science, it was for data analytics which is, depending on who you ask, either a different discipline or an umbrella so large that it includes data science among others.
I'm old enough to also remember data processing turning into data analysis, expert systems, data mining and so on. Statisticians were off working on chalkboards and hand-fitting fitting curves with calculators during all of this. Once the stats folks started realizing, sometime in the 2000s, the Computer Science had made better and more predictive tools and was a better approach for many observable phenomenon, statisticians the world over bundled up all the different disciplines they could claw together in a black hole and shot at these other disciplines, then wrapped it all in the incomprehensible statistics jargon and claimed it as their own shouting Tukey's name to the mountains.
It's not really worth fighting at this point, but this history is revisionist urban legend at best.
Source: I've worked in data disciplines since the 90s and remember when all the roles I used to work in that dated back decades, suddenly required PhDs in statistics as Stats majors flooded the market in the 2000s.