How Data Science will evolve over the next years?

With the hit of the digital revolution, the outlook and the parameters of data science underwent a serious change. The world nowadays is creating more and more data which causes the need and the emergence of new technologies and roles in the field of data science.

One of the notable signs of these changes is the increasing demand for data scientists. One of the world’s largest job and recruiting websites, Glassdoor, ranks data scientist as the best job in the US for 2019 when it comes both to earning and demand. Why is that?

In the first place, statistics and reports estimate that the digital universe will reach 44 zettabytes in the next less than two years. To be able to imagine it, though it is still beyond one’s imagination, this means that there will be 40 times more bytes in the cyberspace than stars in the universe.

Years ago, the term ‘data scientist’ had a very broad meaning and defined a large range of tasks, related to data itself in any way. Nowadays though, it has diversified to a great extent. The amount of data that a company creates and possesses requires a team of experts and professionals, working on different tasks. It is not possible for an individual anymore to cope with the amount of data and the operations and processes that need to be performed by a multi-skilled team.

Data-driven strategy

Although many companies still underestimate the power of data and its managing and utilizing as a part of their business strategies, the truth is that a weak data strategy can literally kill a business. Data comes from and influences every aspect of an enterprise’s structure – marketing, customer experience and relations, finance, risk, etc. A recent report in the UK shows that 80% of the companies are planning to hire a data scientist in 2019, realizing that developing a solid data-driven strategy is essential for their business.

One more thing – when a company is assessing its data strategy, members of each team have to take part in this process because each one is aware most of what type of data is important for their department.

The unstructured data and the role of data science

As we already mentioned, the data we had before was small in size and therefore easier to structure. It could be analyzed by simple BI tools. A survey shows that by 2020 when there will be much larger amounts of data, as much as 80% of it will be unstructured. BI tools are not capable of processing this volume and variety of information. That is why the role of data science and that of a data scientist have become so essential in the last few years and will be even more in the years to come.

Data Science is a blend of various tools, algorithms, and machine learning principles, aimed at discovering hidden patterns from the raw data. A data scientist not only explores and processes the history of data, but looks at data from many different angles. They usually use advanced machine learning algorithms to identify the occurrence of a specific event in the future. So, data science is used to make decisions by using: predictive casual analytics, prescriptive analytics, and machine learning. To make it even more clear, data science is a more forward-looking approach. It is based on analyzing the past (or the present) in order to make informed decisions in predicting particular future outcomes.

Will AI and machine learning play a bigger role in data science in the future?

There are fears that AI and machine learning can minimize the role of a data scientist in the future. But this is far from any company’s purpose right now. Replacing human intuition is beyond the present ambitions of automation. Artificial intelligence will become even a more powerful tool to assist data scientists, but won’t replace them for sure. We are generating so much data that in the next few years neither a data scientist (or a team) would be able to process it, nor any machine or AI tools could cope with it on their own. So, the only way to get control over data and utilize it for the betterment of business strategies and development is the combined effort of human and AI power. AI can make the tedious tasks (a complaint often stated by employees and more often a reason for mistakes).

Undoubtedly over the next years or a decade data science will start playing one of the most prominent roles in business strategy and development. As many as 65% of the companies that were part of a recent survey claim that data science will be the driving force behind their strategic business decisions.