When you hear the term “data science,” chances are you picture today’s technology-saturated, information-reliant age. But, if you stop and think about it, data science can be traced back to the days of the troglodytes. 

Charlie Waters examines this interesting historical take in a recent Datanami article, in which he defines data science as the process of extracting knowledge from data and offers cave paintings as one of the earliest examples of the discipline at work. These early records enabled humans to track animal movements and understand environmental patterns. 

Cave paintings depicted large amounts of complex information. For example, area maps and astronomical charts. Some historians believe they were created to record and store this information so future generations could utilize it. 

Data science became more sophisticated as humans evolved and began to form civilizations. For example, ancient Egypt conducted the first census, utilizing the information to track trade routes and tax citizens. 

Data Science in the Middle Ages 

According to Waters, data science was deployed in the Middle Ages to track diseases and determine how to prevent the spread. This was a significant public health breakthrough, the implications of which we are still benefiting from today. Check out this previous APEX of Innovation post for more on how technologies can help in the fight against contagious diseases.

Data Management in the Medieval Era 

The invention of the printing press signaled the next wave of data science innovation. The technology facilitated the mass production of books, making it easier for more people to read and record information and leading to data collection on a much larger scale. 

Data science became even more critical during the industrial revolution when factories began collecting data on production rates, quality control, and other factors. This information was used to improve efficiency and optimize production—which continues to track today. 

Modern Data Science

Data science continued to evolve throughout the 20th century, with the New York Times declaring 2012 as its crossover year into big business. The technology has matured significantly in the ensuing decade and will no doubt continue to innovate in the years ahead.

Take a look at the Datanami piece for more on what we can expect in the future, as well as additional examples of data science from human history.