Agility is the capacity to have a "conversation" with data. Watson was in a sense having a conversation with "Jeopardy!" host Alex Trebek. But the computer was also having a conversation with its data store, creating a series of answers with varying degrees of certainty.

Businesses successfully utilizing big analytics can take this process of knowledge discovery even further, identifying questions, exploring the answers and asking new questions based on those answers. This iterative quality of data analysis, rather than incremental exploration, can lead to a deeper understanding of business and markets, and begin to answer questions never before considered.

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Watson was also able to understand the intricacies of human language, in many cases even the semantics of puns and wordplay. While database analytics solutions of course can't understand language, the ability to understand complex questions, and explore gargantuan data stores, is indeed critical.

Bringing these big analytics traits together for (ERM), now a central focus for companies, is one example. Exploring risk across the organization, companies glean the "risk web" that shows causality and not simply correlation among various risky actions. Analyzing this risk web in order to make sound decisions, often in a short timeframe, requires an analytic platform delivering on the promise of big analytics.