Covering Disruptive Technology Powering Business in The Digital Age

The amount of data in our world is growing at an unprecedented rate but at the same time many companies are struggling to turn that data into valuable insights. A key problem is the lack of people with the right analytics skills. The demand for data scientists is said to outstrip supply by a factor of three to one.

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

To make this technology more widely available and give more people access to analytics, IBM is today announcing a new student edition of its Watson natural language analytics platform as well as an expansion of its academic initiative to get their technology into education programs around the world.

More than 400 universities are already using the technology as part of data analysis programs, but today’s announcement will increase Watson’s footprint in academia even further. Dr Martin Block of Chicago’s Northwestern University – a member of the Watson Analytics Academic Program, says, “Data analysis will be a critical part of every job in the twenty first century.”

While most people can see how certain information would be useful and what sort of insights might be derived from it, many 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 even more often they lack the analytical skills to tell that computer what to do. In essence, NLP is teaching computers to accept that input in the natural, spoken language of humans – breaking down the communications barrier between man and machine.

This article was originally published forbes.com and can be viewed in full here

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