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Data has been a hot topic with the advent of the information age in the 21st century. This was followed by the birth of “data scientists”, an occupation to manage this inflow and information and to attempt to put it to the best possible use. Although the term data scientist is relatively new, this task was earlier referred to as data mining. The amount of data being generated is staggering and can be used in order to drive business decisions. This is where data science has a crucial role to play and the manner in which its future will shape up is of great significance.

 

Automation of Data Science

With the rise of machine learning and artificial intelligence, a lot of work in data sciences will get automated. However, automation will not replace critical human competencies that make data scientists so valuable to their organizations. Data scientists will have to focus on the application of this data by first, choosing the right problems to solve and apply the data to, second, effectively conveying the results of the data analysis and finally, understanding the ethical implications of their work.

 

Data Science Specialists will become a norm in Companies

Earlier, data scientists were required to oversee each and every aspect of the data analysis lifecycle, right from data collection, analysis, and visualization. However, with the huge inflow of data and the wide array of uses that it can be put to, specialists are required at every link in the chain of data analysis.

 

The Advent of Deep Learning

Machine learning and artificial intelligence have been employed in order to achieve deep learning. In 1997, IBM’s Super Computer Deep Blue beat Chess Champion Garry Kasparov, but Deep Blue was taught how to play chess by chess grandmasters. However, recently Google created an artificial intelligence which beat Go World Champion Lee Sedol. The fascinating phenomenon is that Artificial Intelligence taught itself to play Go. Thus, deep learning not only runs code but keeps developing nuanced and innovative approaches to deal with complex data questions.

With the revolution in technology, growing trends have shown that data science has now begun to spread beyond what it was originally conceived for and it is no longer limited to giant tech firms, but all sorts of industries are recognizing and profiting from the massive collection of data. This, in turn, creates a myriad possibility of jobs for data scientists and associated tasks.