The start of modern data science can be traced back to Google search ranking optimization and for LinkedIn recommendations. But now data science is used across all fields. Yet, the terms data science and data scientist aren’t that well understood. One of the key tasks for data scientists is to build a solid foundation on which business analytics may be performed. Machine learning pipelines and personalized data-backed products then need to be worked on. Contrary to the usual perception, data science is now being performed in several industries beyond tech, such as healthcare, travel bookings, restaurants, ride-sharing and much more. More than tall promises such as artificial intelligence or autonomous cars, it is about facilitating the daily processes. The skills needed by data scientists is also constantly evolving. At present for instance, a disproportionate amount of time is getting spent on cleaning and optimizing the data. Specialization is getting increasingly important. Data science is now being worked on in three broad areas which are- business intelligence, decision science and machine learning. A major challenge right now and only expected to expand is the ethics in the field. Privacy and data protection are two of the crucial aspects where ethics could get challenged.


Uploaded Date:27 November 2018

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