Cognitive analytics simulates human thought processes to learn from data in real-time. It uses data mining, pattern recognition, and natural language processing with both supervised and unsupervised machine learning techniques in order to identify patterns and anomalous behaviors that are often unexpected, important, and influential.
The applications for the technology are many, and it’s set to transform business, driven largely by an explosion in the adoption of cognitively enriched intelligent machines like IoT and mobile devices. Cognitive systems learn through experience, and apply what they’ve learned to new inquiries or tasks, making them far better suited for the next explosion of data that connected devices, which traditional algorithm-based systems will struggle to deal with because they are limited by their pre-programmed settings.
The IBM Watson machine is the prototype of this type of computing. Watson has access to a vast store of historical data, which it then applies machine learning algorithms to in order to pinpoint connections and correlations. This forms a so-called ‘knowledgebase’ which provides an engine for discovery, decision support, and deep learning. It uses this to provide answers to queries at the right time, in the right context.
IBM is clearly confident that Watson is the future, having invested north of a billion dollars in its development. The International Institute for Analytics (IIA) has also predicted that cognitive technology will succeed automated analytics as the next big thing in data. Despite its relative youth as a buzzword, it is already gaining traction in terms of take up. In a recent IBM Institute for Business Value study, ‘Redefining Competition: Insights from the Global C-suite Study - The CEO perspective’, 11% of CEOs surveyed said they were already using cognitive computing technology in their businesses. These numbers are promising, but they do not indicate a technology that is simply going to blow up. If it’s going to be like other disruptive technologies, it’s likely that it will be introduced slowly as people gauge how exactly it can boost their business. This is especially likely because of its ties to IoT, which has yet to take off as many believe it eventually will.
There are numerous applications for cognitive analytics that spring to mind though. Cybersecurity is one that we have previously covered (https://channels.theinnovationenterprise.com/articles/cognitive-computing-takes-on-cyber-security). Healthcare and banking are two others, fields where the amount of data is truly unmanageable and where accurate decisions are required immediately. Even Airbus has identified where it could be of benefit to them, with Laurent Martinez, head of its business unit services, telling IBM's Watson Internet of Things global headquarters in Munich: ‘I’m deeply convinced that the future of aviation is about data, it's a big, big future.’ He noted that an Airbus aircraft consists of more than 300 million parts, and on many of the newer models these parts are collecting data throughout flights, which Martinez said offered ‘a new generation in terms of understanding how an aircraft will behave.’
With the volume of data that cognitive analytics can deal with at speed, as the number of connected devices explodes it will become vital, whether companies know it yet or not.