It is just a re-branding of the Data Analytics of 10 years ago, the Data Mining of 20 years ago and the Business Intelligence of 30 years ago.
We’ve been doing machine learning (SVM, ANN, Decision trees, etc) and ETL to analyze data and produce valuable information for decision making for 20+ years now, but all of a sudden giant techs like Facebook and Google decided the title “Data Analyst” was not sexy enough, maybe because the growth of CPU power and the advent of the GPU for numerical calculations pushed the boundaries of the algorithms, e.g. deep learning, either that or they had so many PhD’s enrolled doing data analysis that they wanted to honor their job with a more coveted title.
The truth is that someone with a PhD in Statistics working at YouTube in 2006 was already employing cutting-edge stats and machine learning to find patterns in the data, but was just called a Data Analyst. 7 years later that same guy still working at YouTube doing data analysis was now called a Data Scientist. Did he care about HR changing his job name? Absolutely not. He just went on doing what he loves and ignoring fancy marketable titles like “Data Scientist”.
Oh, and also the fact that Data Science is not Science per se, since no one is following the scientific method to produce new theories that can be reproduced or falsified, nor adding to the corpus of knowledge of the field. We are merely using methods from science to aid us in our daily task, which I repeat is: producing valuable information to the Business for intelligent decision making. In this aspect a Data “Scientist” is more akin to an engineer using science rather than a physicist producing new theories.
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