The evolution of Data Science … as I remember it


This post was originally published by Charlie Kufs at Towards Data Science

Featured images by Chuttersnap on Unsplash

Things have changed a lot in fifty years.

Anonymous feline in witness protection program.

Those who cannot remember the past are condemned to repeat it.

George Santayana

Feline crunching on number keys.

“For a long time, I have thought I was a statistician, interested in inferences from the particular to the general. But as I have watched mathematical statistics evolve, I have had cause to wonder and to doubt…I have come to feel that my central interest is in data analysis, which I take to include, among other things: procedures for analyzing data, techniques for interpreting the results of such procedures, ways of planning the gathering of data to make its analysis easier, more precise or more accurate, and all the machinery and results of (mathematical) statistics which apply to analyzing data.”

One of my cohorts and I discussing data science.

No single statistician can be expected to have a detailed knowledge of all aspects of statistics and this has consequences for employers. Statisticians flourish best in teams-a lone applied statistician is likely to find himself continually forced against the edges of his competence.

M.J.R. Healy. 1973. The Varieties of Statistician. J. Royal Statistical Society. 136(1), p. 71–74.

Waiting for the mainframe to print out my analysis.

Feline PC watching feline mainframe.

Big Data cat.

Data Scientist means a professional who uses scientific methods to liberate and create meaning from raw data. … Statistics means the practice or science of collecting and analyzing numerical data in large quantities.

To a statistician, [the definition of data scientist] sounds an awful lot like what applied statisticians do: use methodology to make inferences from data. … [the] definition of statistics seems already to encompass anything that the definition of Data Scientist might encompass …

The statistics profession is caught at a confusing moment: the activities which preoccupied it over centuries are now in the limelight, but those activities are claimed to be bright shiny new, and carried out by (although not actually invented by) upstarts and strangers.

Feline data scientist observing feline statistician.

“… rather than attracting individuals from new demographics to computing and technology, the growth of data science jobs has merely creating [sic] a new career path for those who were likely to become developers anyway.”

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This post was originally published by Charlie Kufs at Towards Data Science

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