Cognitive Analytics is intelligent technology that covers multiple analytical techniques to analyze large data sets and give structure to the unstructured data.
To put it simply, a cognitive analytics system searches through the data that exists in its knowledge base to find real-time solutions (solutions that make sense) for the questions posed.
Cognitive analytics can be thought of as analytics with human-like intelligence. This can include understanding the context and meaning of a sentence, or recognizing certain objects in an image given large amounts of information. Cognitive analytics often uses artificial intelligence algorithms and machine learning, allowing a cognitive application to improve over time. Cognitive analytics reveals certain patterns and connections that simple analytics cannot.
An organization might use cognitive analytics to monitor their customer behavior patterns and emerging trends. This way the organization can predict future outcomes and plan their objectives accordingly to improve their performance.
Some sections of cognitive analytics also fall under predictive analytics, where data in business intelligence is used to make predictions.
Real-Life Applications of Cognitive Analytics
The medical industry is now starting to use cognitive analytics to match its patients with the best possible treatments. Some examples of cognitive analytics which are in use today include Microsoft’s Cortana, Apple’s Siri, and IBM’s Watson.
Organizations are using cognitive analytics to tap into unstructured data sources such as images, emails, text documents, and social posts.
Though cognitive analytics is still in its infancy, it may be the solution to finding real-time answers for large amounts of diverse data, and bringing a paradigm shift from traditional analytics.