Watson and Big Data

On February 15, 2011 IBM’s Watson Supercomputer, according to, “defeated humanity” in Jeopardy. While the world was impressed when IBM’s original supercomputer beat a Grand Champion in chess, winning a game as dynamic and nuanced as Jeopardy was truly a landmark occurrence. Winning at Jeopardy requires not only processing vast amounts of data, but also necessitates natural language understanding and comprehension. This begs the question: What if every business could ask Watson what to do next?

So, if you want to answer this question, who do you call? Watson? Big Data? Something else?

The answer to this question has 2 parts: a) the Big Data platform/infrastructure and b) the use case and/or application that is built on top of that platform. Graphically, it is as simple as this:

Watson is a unique implementation (think high powered use case) of Big Data. Watson leverages Hadoop and other technologies that are a part of IBM's Big Data Platform. However, this does not mean that Big Data = Watson. Instead, as described above, you should think of Watson as an extraordinary corner case of function, built on a Big Data infrastructure.

To extend the thought, you should think of a Big Data Platform as infrastructure that would simplify the use of a Watson-like use case or other use cases. The platform ingests and annotates a variety of data types, can process them in real-time, and can do this at a massive scale. Once that is complete, that data is ready to be acted on, whether it is needed to determine your next best action, improve your IT operations, or play Jeopardy.

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