Pushing ARTIFICIAL INTELLIGENCE ahead: the practical business value of cognitive visualizations

Search and data discovery

Immersing oneself within one’s data also delivers unrivaled capabilities for both data discovery and search. Boris says, “There are some interesting use cases emerging around visualizing data or code in three dimensions to detect anomalies pertaining to cognitive visualizations.” Fully immersive technologies such as VR are remarkable because they deliver insight in layers. The first specifically pertains to the answers for which a user is conducting a search. The second, which could prove even more influential, is what Green calls “incidental insight” and correlates to discovering previously unknown aspects of data’s importance for use cases. According to Green, “Search is the one area that we’re seeing the most interest in—being able to see not only what you’re looking for but also how it relates to other items as well.”

The 3-D approach of cognitive visualizations is especially effective on complicated datasets, which become time-consuming to effectively visualize with conventional 2-D methods. The classic use case for taming that sort of complexity exists in life sciences. Green recollects a bioinformatics example in which there were “datasets with 20-plus dimensions of a couple hundred thousand nodes. To analyze those with [the user’s] existing methods was a two- to four-hour process. We were able to bring that down to about 15 minutes.”

Other facets of data discovery are radically improved by the AI input modes of cognitive visualizations. Because users can affect their discovery and search processes with those sensory inputs, they can expand their awareness of data and its underlying context. “The ability to spot things that you may not have known you were looking for is where VR really speeds things up,” Green says. For instance, simply by inadvertently moving one’s head in a certain way while visualizing data in 3-D, users gain perspectives they otherwise wouldn’t about how data relates to business problems. Those AI inputs are an integral part of cognitive visualization advantages. “XR is allowing people to bring in all the ways that we take in data naturally,” Green says. “There are ways to plug those into the visualizations.”

Interactive personalization

Perhaps the unifying theme between all of the various use cases outlined in this article is that either directly or indirectly, cognitive visualizations heighten interactions between users and their data. Regardless of location, IT system or business functions, the visualizations provide details of the most intimate aspects of data systems—whether those involve an automotive engine, financial analyst data or the ornate interstices of computational biology models. In almost all use cases, they reduce time and human resources dedicated to solving business problems, while facilitating new methods for streamlining processes to generate business value.