Cognitive Computing has carved out new possibilities and reaches for machine learning in Human Computer interaction models and problems. Cognitive analytics is one such derived application of cognitive machines. Before venturing into the applications and use cases of cognitive analytics, we should pause for a moment to reflect on the essential nature of cognitive analytics. Analytics aided by cognitive computers opens up possibilities to apply human like analytic techniques to data driven problems. It is interesting to think about a cognitive method to analytics.

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Cognitive analytics is not just about employing a powerful cognitive computer like Watson. When you analyze cognition and why and how human mind applies cognition, we should realize that it is a matter of evolutionary learning and survival strategy. Rather than understanding every problems and every situations time and again, mind has realized that it is efficient to memorize the situation ( context ), problem ( trigger ), algorithm ( operation ), and result ( outcome ).

Have you ever thought about the difference between cognition and recognition? When we recognize something or someone, we are applying our cognitive capabilities quite intuitively and collectively. Cognition is structured like a very flexible and modular scheme of things. Our brain stores the cognitive algorithms, results of each cognitive operations, the input parameters to cognitive operation etc in a relational manner.

Thus we can see that cognitive analysis is more context intensive than data intensive. Cognition analyses more of context, associated cognitive operations and related outcomes of cognitive operations. It is not just about immersing a powerful algorithm to break down a humongous data set. Hence a rational reflection on the human strategy of cognitive operations will help us to design an analytic scheme leveraging cognition.