Learn about cognitive analytics and how it can help machines achieve human-like intelligence.

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.

The majority of data that organizations deal with is unstructured. Making sense of it, to make it available for your business priorities, namely, for decision making is beyond our human capacity at the scale of our information. Cognitive computing brings together a number of applications to reveal context and find answers hidden in large volumes of information.

Cognitive is a set of mental processes that are performed by the brain and analytics is nothing but a computerized analysis of the data. Since cognition is related to the human mind, it is nothing but the usage of human-like intelligence as its foundation. This is combined with artificial intelligence, machine learning, semantics, and deep learning to compute different types of data.

One of the most pertinent problems that organizations face globally is to make meaning out of the data, which is usually unstructured and scattered across the globe. Since it is practically impossible for a human brain to compute such a vast volume of data, which is why we have cognitive computing. By using cognitive computing, enterprises can leverage multiple tools and applications to make contextual inferences of their data and come up with analytics-driven information from this huge quantum of data.

All these inferences bring us to data analytics, which also incorporates descriptive analytics. Today, we know that both Prescriptive Analytics and Predictive Analytics are decade-old technology. Thanks to these technologies, today we see many intelligent technologies gaining a strong foothold. To help these modern technologies like cognitive analytics to realize their importance, there was a major contribution from the Artificial Intelligence Conference that was held at Dartmouth College in the year 1956.

Cognitive analytics is a data-forward approach that starts and ends with what's contained in the information. This unique way of approaching the entirety of information (all types and at any scale) reveals connections, patterns, and collocations that enable unprecedented, even unexpected insight.

Applied in the enterprise, cognitive analytics can be used to bridge the important gap between large volumes of information and the need to make decisions in real-time. A deep understanding of information helps companies draw from the wide variety of information sources in their knowledge base to improve the quality of enterprise knowledge, competitive positioning, and provide a deep and personalized approach to customer service.