Data science is a field focused on extracting knowledge from data. Put into lay terms, it is obtaining detailed information applying scientific concepts to large sets of data used to inform high-level decision-making. Take the ongoing COVID-19 global pandemic for example: Government officials are analyzing data sets retrieved from a variety of sources, such as contact tracing, infection, mortality rates, and location-based data, to determine which areas are affected and how to best adjust on-going support models to provide help where it is most needed while trying to curb infection rates.
Big data, as it is often called, is the collective aggregation of large sets of data culled from multiple digital sources. These swaths of data tend to be rather large in size, variety (types of data), and velocity (the rate at which data is collected). This is because of the explosive growth and digitization of information globally and the increase in capacity to store, handle, and analyze data pools of this magnitude.
Jim Gray, a computer scientist and Turing Award recipient, imagined data science as the "fourth paradigm" of science—adding data-driven after empirical, theoretical, and computational. With this in mind, the programming languages here are poised to be efficient in their handling of large data sets and robust in their coalescence of multiple data sources to effectively extract the information necessary to provide insight and understanding of the phenomena that exist within data streams for data mining and machine learning, among others.
Python
Lauded by software developers and data scientists alike, Python has shown itself to be the go-to programming language for both its ease of use and its dynamic nature.
R
R is often compared to Python in that its inherent strengths are similar because of its open-source nature and system-agnostic design to support most operating systems. And while both languages excel in data science and machine learning circles, R was designed by and leans heavily into statistical models and computing.
Java
Java has been around for about a quarter of a century, and, during this time, the class-based, object-oriented language has adhered to the "write once, run anywhere" creed, establishing it as requiring as few dependencies as possible—regardless of where its code will run.
Julia
Compared with the other programming languages on this list, Julia is the newest language with less than 10 years since its initial release.
Scala
A high-level programming language that is based on the JVM platform, Scala was designed to take advantage of many of the same benefits as Java and address some of its shortcomings.