Although data science has been around for quite some time, it did not hit the peak of its existence until approximately two decades ago. Ever since then, it remains one of the most productive, most useful, and most advanced resources that people from all professional backgrounds can rely on. To get a sense of just how widespread it is, consider the fact that it is easier to name the markets that do not use data science than it is to list the ones that do.
As with every contemporary resource, a lot of specialists are curious about the longevity of data science. After all, many experts thought that DVD rentals would be a timeless solution to live television. When online streaming was invented, however, DVD rentals became obsolete, and what appeared to be a seemingly unbeatable solution lost the battle to a more innovative alternative. Is it fair to expect that data science will face the same destiny? In other words, will it exist once someone invents something new?
Data science is a field that revolves around interpreting structured and unstructured sets of information. Although the official name for it came in the early 2000s, the actual practice has been around for much longer. Nonetheless, it is fair to mark the beginning of the 21st century as the starting point for data science that people utilize nowadays. This is mostly because the current century is when everything from the modernized internet to the very first smartphone came to life. Because of such developments, data science began growing as a practice.
The Evolution of Data Science
With the introduction of powerful technology, which continues to get better each year, data science received the biggest boost of its lifetime. Instead of conducting analyses via print mediums, experts slowly transitioned to computers. By employing a wide variety of data programs, the pioneer of which would be Excel, people could now go through larger sets of information with unprecedented speed. Almost two decades later, most operators traded Excel for tools that are even more efficient and effective. So, while the resources have certainly improved, the overall presence and purpose of data science remain the same. Thus, besides changes pertaining to the techniques of delivery, it is fair to expect that this multi-disciplinary field will continue to exist well into the future.
According to a timeline provided by Forbes Magazine, the term “Big Data” was first used in 1997. Michael Cox and David Ellsworth are credited with inventing this name when they published their paper on “Application-Controlled Demand Paging for Out-Of-Core Visualization.” Since then, Big Data has developed more than any data scientists from a few decades ago could predict. Even though many experts claim that the state-of-the-art resources that currently exist are the peak of innovation, further advancements will most likely prove them wrong. Consequently, while it is impossible to predict what exactly will come next, it is safe to say that data science tools will only get better.
Based on the track record that information analysis has, it will likely be around for a long time. Not to mention that there are no alternatives that could effectively replace it. Nonetheless, trying to predict the exact year until which data science will exist is impossible.
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