The future has arrived. Today, computers can nearly mimic the human mind’s ability to learn, think, reason, analyze and make decisions. This technology is called cognitive computing.
Often, cognitive computing is confused with other emerging data science advancements such as business intelligence (BI), deep learning (DL) and machine learning (ML).
However, what differentiates cognitive computing from these other amazing technologies is that it can read and comprehend “dark data.”
Dark data is commonly known as unstructured information.
This kind of data is not conducive to analysis by BI, DL or ML technologies. As a result, cognitive computing is vitally important, as technology experts report that unstructured data represents 80-percent of the sum of the world’s digital information.
Resultantly, enterprise leaders need skilled data science professionals who can prevent information bias, leverage unstructured data for decision-making and increase the speed and accuracy of data analysis. Despite the ability of cognitive technology to “think,” this kind of resource always requires a skilled operator.
Humans must always be in control and have the ability to explain to stakeholders how data is being used, how it’s managed it how it’s protected. No matter how advanced the technology, humans must stay at the helm to ensure security and safety.
Big Data and Cognitive Disruption
According to a recent IBM report, unstructured data will represent 90-percent of all information as soon as 2020. This information comes from images, sensors, videos, audio files and telephony data.
Cognitive systems build on current advanced big data technologies by reducing much of the programming required to perform effective analyses.
Prior to this innovation, data scientists had to explicitly program systems to perform desired functions. Because of this, analysis frameworks prior to cognitive systems couldn’t perform outside of programmed scenarios.
Alternatively, cognitive analysis systems have critical thinking abilities that mimic the human mind. They analyze, learn and understand, without the need for programmer intervention. Still, the foundation of cognitive computing lies in assisting mankind – not replacing it.
IBM’s survey revealed that 73-percent of polled CEOs from around the world plan to deploy cognitive computing in their operations. Additionally, 75-percent of the group believes that cognitive technology will disrupt their industry soon.
Creating a New Discipline for Marketers
In marketing, advanced analysis technologies magnify the abilities of professionals working in the field. As an example, personalization, consumer-centric strategy and long-term relationship building are essential for promoting sustainable positive enterprise outcomes.
Advanced analysis systems help marketers deliver the right messages to the right customers at the right time.
In addition, technologies such as cognitive computing help marketing professionals discover opportunities that no human being could ever hope to find using manual research methods. By extrapolating data from social media sites, email communications and website metrics, marketers can leverage advanced analysis systems to build a strong rapport with and create valuable experiences for their audiences.
Still, cognitive systems have a long way to go before mastering emotional intelligence and creativity.
For now, enterprises need skilled marketers for their storytelling and creative skills to create messages that resonate with potential buyers.
Data is still key to understanding consumer behavior, but with advanced data analysis systems, marketers can make sense of seemingly immeasurable amounts of information and drive corporate success. While data analysis provides insight, marketers turn those insights into actions that produce tangible value.
Impacting the Road Ahead
Advanced technologies such as cognitive intelligence, predictive analytics and machine learning build on the foundation of big data systems. Now, with the introduction of cognitive intelligence technology, cutting-edge data analysis systems emulate the complexity of the human mind.
Today, data scientists must teach cognitive intelligence technology how to learn. Tomorrow, the technology will teach itself.
The number of executives who plan to leverage this remarkable new technology in 2019 may seem astounding, but the reasoning behind this is crystal clear. Still, deploying cognitive intelligence systems in conjunction with existing enterprise analysis technology will prove challenging.
IBM’s Watson technology, for instance, took decades to assemble, cost hundreds of millions of dollars and required the work of thousands of highly talented engineers.
For now, this bleeding-age technology will be inaccessible to all but the most resource-rich enterprises. Still, some firms who are not quite within the upper echelon of corporate influence may be able to leverage the technology by partnering with the right software-as-a-service (SaaS) vendor.
In the IBM survey, the executives who reported the largest economic benefits believe that advanced technologies, such as cognitive intelligence, are best leveraged for transformational rather than incremental change. In other words, executives believe that cognitive intelligence is a tool for disruptive transformation.
Early adopters of cognitive technology expect that the innovative resource will have a major impact on commerce.
Already, advanced analysis systems are heavily impacting and changing how enterprises conduct business. If this trend continues, advanced analysis systems may live up to the hype promoted by the global media and the world’s information technology service notice he got me all stirred of this will be to first falcon thing on my mind in the morning providers.