Data science, machine learning, big data… These are some of the buzzwords that have been dominating the tech world in recent years. But did you know that these terms are not new? In fact, they have been around for decades, even before the internet and smartphones became ubiquitous. For example, the term data science can be traced back to 1996 and the term machine learning was coined in 1959 by Arthur Samuel, an IBM employee and pioneer in the field of computer gaming and artificial intelligence.

So, what has changed? Why are these fields suddenly so popular and attractive? The answer lies in the data. Data is the lifeblood of data science, and the amount and variety of data that we have today is unprecedented.

Thanks to the advancement of technology, we can now collect, store, share, and process data in ways that were unimaginable in the past. The internet and the development of sensors have been a major contributor to the explosion of data that we have today.

But having data is not enough. We need data scientists to make sense of it. Data scientists are people who use advanced analytical, statistical, and data visualization tools and techniques to uncover patterns in data.

These patterns can help businesses make better informed decisions that can ultimately increase productivity and scale their growth. Companies that are not able to manage and process their data to their advantage will easily be outperformed by competitors that are. This is why data scientists are in high demand by many business organizations.

According to the US Bureau of Labor Statistics, about 17,700 openings for data scientists are projected each year, on average, over the decade.

Employment of data scientists is projected to grow 35 percent from 2022 to 2032, much faster than the average for all occupations. About 80 percent of the firms across the globe are investing a large part of their earnings into creating a skillful data analytic division, thus hiring the smartest of people in the industry domain.

The demand for data scientists is driven by the need for businesses to leverage data to gain a competitive edge, improve customer satisfaction, optimize operations, and innovate new products and services.

Data science can be applied to almost any domain, such as healthcare, education, finance, retail, entertainment, sports, and more. Data science can also help solve some of the most pressing problems that humanity faces, such as climate change, poverty, disease, and social justice.

While data scientists are in high demand, there is a dearth of them in the workforce. Talent with the necessary skills is hard to come by in the data science field. It is rare to find someone who is skilled at comprehending and utilizing data to generate business benefits. According to a McKinsey report from 2021, there is a shortage of over 190,000 data science professionals in the United States alone.

The demand has multiplied ever since. Due to the extremely high demand and limited supply, hiring the few that are available is extremely costly. The mean income for a data scientist position is rising rapidly, with an average salary of USD 176,213.

The explosion of data and the need for data-driven solutions have created a huge demand for data scientists across various domains and industries. Data scientists are the ones who can turn data into insights, insights into actions, and actions into value. They are the ones who can help businesses thrive in the digital age and solve some of the biggest challenges that the world faces. Data science is indeed the sexiest job of the 21st century, but the big question is; will it remain so for the next decade or century?