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 to do so 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. If you’re looking to apply intelligent technologies in your business, cognitive analytics is a great place to start. In this post we answer the question: what is cognitive analytics?
Since the now infamous artificial intelligence conference at Dartmouth College in 1956, intelligent technologies have been slowly gaining ground. By 2019, IDC projects that the worldwide market for cognitive software platforms and applications will grow to about $16.5 billion, up from $1.6 billion in 2015.
Intelligent technologies are uniquely positioned to address the new enterprise data reality of high volume, multi-source, primarily text-driven information. According to IDG’s “Big Data and Analytics: Insights into initiatives and strategies driving data investments, 2015”, enterprises that adopt data-driven projects use primarily unstructured data sources such as customer databases, email, transactional data, worksheets and Microsoft Word documents.
For many organizations, however, this is just the tip of the iceberg in terms of the available resources. Open source information available on the internet such as regulatory and patent information, census data and social media posts are a valuable part of the information ecosystem. Add in Internet of Things type data from sensors and you have a level of complexity that is both a challenge and an opportunity.
The risk of leaving this information on the table is too great; thanks to today’s abundance of fast, cheaper computing power, the application of intelligent technologies such as cognitive analytics is more accessible and more affordable than ever before.
What is cognitive analytics?
Cognitive analytics applies intelligent technologies to bring all of these data sources within reach of analytics processes for decision making and business intelligence. Here’s how:
What is cognitive analytics? Intelligent analytics
Cognitive analytics applies human like intelligence to certain tasks, such as understanding not only the words in a text, but the full context of what is being written or spoken, or recognizing objects in an image within large amounts of information. Cognitive analytics brings together a number of intelligent technologies to accomplish this, including semantics, artificial intelligence algorithms and a number of learning techniques such as deep learning and machine learning. Applying such techniques, a cognitive application can get smarter and more effective over time by learning from its interactions with data and with humans.
What is cognitive analytics? Analytics that puts data first
Cognitive analytics is a data forward approach that starts and ends with what’s contained in 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 your knowledge base to improve the quality of enterprise knowledge, competitive positioning and provide a deep and personalized approach to customer service.
