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Will We Soon No Longer Need Data Scientists?

http://www.datasciencecentral.com/profiles/blogs/will-we-soon-no-longer-need-data-scientists

The job of data scientist — the quintessential big data job, and the job that was just voted the best job in America for 2016 — is at risk.

Data scientists have been called “unicorns” because finding the right person with the right set of skills — including coding, statistics, machine learning, database management, visualization techniques, and industry-specific knowledge — could be practically impossible.  But machine learning and big data itself may be making those unicorns as obsolete as they are mythical.

New machine learning algorithms can autonomously analyze data and identify patterns, even interpret the data and produce reports and data visualizations.

You (and your computer) can be your own data scientist

While most people can see how certain information would be useful and what sort of insights might be derived from it, most lack the technical skills to perform the analytics. They might not have the computers that are able to carry out the large volume of calculations quickly enough to take action, but more often they lack the analytical skills to tell that computer what to do.

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Natural Language Processing (NLP) technologies can help to break down the barriers to widespread use of data analytics by making complex analytics possible to just about anyone, regardless of their technical ability. In essence, NLP is teaching computers to accept input in the natural, spoken language of humans – eliminating the communications barrier between man and machine.

IBM, for example, believes that it can offer a solution to the skills shortage in big data by cutting out the data scientists entirely and replacing (or supplementing) them with its Watson natural language analytics platform.

IBM’s Vice President for Watson Analytics and business intelligence, Marc Altshuller, explains “With a cognitive system like Watson you just bring your question – or if you don’t have a question you just upload your data and Watson can look at it and infer what you might want to know.

“A traditional data scientist might receive training in R or SAS or whatever tool their school uses, but we found in the ‘citizen analyst’ area, they were often being given the wrong tools where they were required to guess the right answer, and then test their guess.”

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I believe that Watson, and other NLP or cognitive technologies, will play an important role in the future of analytics and the education around it.

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