The Brief History of Data Science

Data science is a rapidly growing field and there are many opportunities available for upcoming data scientists. In fact, according to the Bureau of Labor Statistics, data science jobs are projected to grow 36% between 2021 and 2031. As many people consider data science as a possible career, it is important to understand the history behind it. 

Firstly, what is data science?

As IBM describes, “Data science combines math and statistics, specialized programming, advanced analytics, artificial intelligence (AI), and machine learning with specific subject matter expertise to uncover actionable insights hidden in an organization’s data.” This essentially means that data science is a field that combines elements of programming and computer science with statistics that provide meaningful conclusions from a particular data set.

Early data science entailed using mathematics to analyze data. Later, in 1962, John Tukey explored the conjunction between statistics and programming. He wrote multiple papers, such as The Future of Data Analytics and Exploratory Data Analysis, that delve deep into data analytics. In 1974, Peter Naur published Concise Survey of Computer Methods, which explored data processing methods. In the coming decades, many people around the world ventured into data science and its uses. 

In the 2010s, data science started growing rapidly. Many companies began hiring data scientists. As shown in the photo below from LinkedIn Analytics, data science jobs started growing rapidly in the 2000s and had a sharp climb around the year 2010.