What are the Characteristics of Cognitive Analytics?
The basic characteristics of cognitive analytics include the use of a modeling system that analyzes the way humans process thought.
Cognitive analytics also serve an important function that provides visible models of human learning. It is especially useful in applications based on artificial intelligence, virtual reality and language learning systems. Other characteristics include the ability to mimic human brain patterns through data mined information.
Useful Characteristics
The use of this type of analytics has the greatest effect on human thought patterns by linking various human actions. Computers store data in memory, analyze it and apply the results to various software applications. Opportunities exist for interactive computer to computer data to perform tasks humans can’t due to lack of knowledge or inability to adapt to language differentials.
The speed with which data can be analyzed and processed makes it possible for businesses to make optimal decisions at critical points in transactions. Because the analytics are initially created with models, the user has access to visible proof of several possible choices. Left to a human analytical group, the results are limited by comparison.
Analytics for Artificial Intelligence (AI) Applications
Perhaps the most useful characteristics of these analytics are in applications related to artificial intelligence where speech recognition is frequently necessary. It is easy to see how those in the legal, medical and science businesses benefit from software applications that reduce the need for human action while storing vast amounts of analyzed data that is ready for use.
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