Data science has been around in various forms since the dawn of computing, but it has only become part of the public consciousness in the last decade or so.
Today, data science professionals are being sought out to solve problems that were previously solved by engineers and statisticians alike, and they’re finding applications in industries as diverse as biotechnology and finance.
With the rise of data science comes an increased need for data scientists, who have expertise across multiple disciplines including math, statistics and engineering.
Data Science has been called the sexiest job of the 21st century, and it’s hard to argue with that designation. But just what are people talking about when they talk about Data Science?
As Gartner defines it, data science is the discipline of extracting knowledge from data in diverse forms and converting data into new insights and strategic direction. So while there isn’t one set definition of Data Science, here are five ways it changes our world today.
1) The Rise of Big Data
The Rise of Big Data has changed the way we do business, interact with technology, and live our lives. It's hard to believe that only a few years ago we were barely hearing the term big data. But in 2009, the release of Google's paper on MapReduce sparked an interest in how it could be applied to big data processing.
In 2010, Facebook released their own paper about a new programming language called Hadoop which used MapReduce as its backbone for big data processing. These papers ignited the rise of both these topics and what is known today as Data Science.
2) The Growth of Data-Driven Companies
The Growth of Data-Driven Companies Data science has become a vital component of business in the 21st century. At the forefront of this trend are data-driven companies, which use data science to help make decisions and develop strategies for their companies.
These organizations have an edge over competitors who are still using traditional methods. The rise of data-driven companies has also led to increased interest in information technology careers as well as increasing demand for individuals with these skills.
Jobs that are commonly found at data-driven companies include engineering, analytics, product management, marketing and advertising professionals, software development professionals and designers. One study estimates that there will be two million (2,000,000) unfilled IT jobs by 2023 due to shortages of qualified candidates.
In addition to providing access to quality employment opportunities for people looking for jobs in the field of data science, working at a company that emphasizes utilizing data can provide employees with opportunities for professional growth.
3) The Proliferation of Data Scientists
The proliferation of data scientists has been a game changer for businesses as they now have the capability to analyze massive amounts of data and turn it into meaningful insights.
Data science also allows organizations to stay ahead of the competition by utilizing new technology and adding more value to their products and services. Data science creates a valuable cycle of innovation that benefits everyone involved, from customers, to employees, and even competitors.
The exponential increase in data sources has increased demand for data scientists exponentially; however, supply isn't meeting the demand yet. In fact, some companies are predicting an up to two hundred percent (200%) shortage of qualified data scientist candidates by 2023.
However, with this current climate comes an opportunity: whether you're a marketer or developer, there are ways you can become more proficient in how you use data to make your organization smarter than ever before.
4) The Advancement of Machine Learning
Machine learning has been around for decades, but the recent advances in artificial intelligence have led to a new wave of success. For example, Google uses machine learning to identify your emails and offer you search results based on the content.
Another example is that self-driving cars use machine learning to identify objects and people on the road. Companies like Ford, Tesla and General Motors are investing heavily in this technology. It is predicted by 2025 there will be thirty million (30,000,000) vehicles with some level of autonomous capability on public roads.
Machine learning also helps drones avoid obstacles and other aircrafts to land safely at an airport, predict power outages using smart grids or estimate crop yields using satellite imagery.
5) The Transformation of Healthcare
The transformation of healthcare has been a long time coming. As the population continues to age and healthcare costs continue to rise, it's become clear that our current system isn't sustainable in the long term.
Recent advancements in data science have enabled us to make advances not previously possible in medicine and thus, we are beginning to see the effects of this shift on our world. With these new tools at our disposal, we can understand diseases better than ever before and use them to be proactive about disease prevention.
Healthcare providers are using data-driven models to identify high-risk patients earlier in their course of care so they can intervene sooner with more appropriate treatments. For example, doctors might prescribe an antibiotic for someone with pneumonia who hasn't been taking their asthma medication as prescribed because they had no idea that there was a connection between the two conditions.
Summary
With the invention of computers, people can now analyze data in new and creative ways. In a matter of seconds, a computer can do things that would take an expert hours or days. This power of data science has led to some amazing discoveries and changes to our world.
