While the major trends in data science include Big Data, Machine Learning, AI, Edge Computing, Digital Twins and Block-chain to name a few. The meshing of physical and real world which drowned the Big Data as well as Data Science, as per industry experts is already drowned by last year’s theme ‘the meshing of the offline as well as online world’ and the trend is going to continue in this year as well.

It’s the year of implementation of the meshing of the physical and virtual world, wherein the advanced data technologies are to take over the routine business process in order to increase productivity and efficiency. The human data scientists will be tackling with the complex challenges. Hence, as far as the responsibilities of data scientists are concerned, they will also continue to evolve into varied roles.

Obviously, the requirement for data scientists, architects and engineers is going to grow. If we go by estimates, it is going to grow by 50 times by the year 2020. Hence, the organizations who already have data science experts with data analytic skills sets will definitely have an upper hand as compared to others. Block chain is another one that is to go mainstream for data protection and detection of fraud


The need for data analytics is spread across sectors like Banking, Healthcare, IT ecommerce, telecommunications and risk management to name a few. The job profile is one of the most lucrative ones as it offers attractive packages. It varies from around 10 lac per annum for the inexperienced to over 20 lacs per annum for people with over 10 years of experience. Hence, these days a lot of institutes offering data science positions are opening up and are in high demand. This is quite evitable from the fact that biggies like Ernst & Young, Deloitte, Accenture, JPMorgan, Adobe and more has the most number of opening for data analysts. On the flip side though, there are experts who are calling data science a double edged sword, where there are chances that the advancement in technology could lead to the wipe out of the requirement of human data scientists probably while the mainstream users of businesses won’t be able to make use of machine guided solutions without taking human expert help. So,

*Sourced from the Internet

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