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Ventana Research today announced new Dynamic Insights research on natural language processing. This initiative will evaluate how organizations are using natural language processing to make information more accessible and understandable as well as the differences between organizations use of natural language generation and natural language query. We also seek to understand how they are addressing difficulties in deploying natural language for analytics and applications.

Natural language can enhance analytics in two critical ways. Organizations can use these capabilities to deliver information and they also can use them to help individuals more easily find and analyze information. The former, natural language generation (NLG), is the process of generating text or narratives based on a set of data values, which can reach a broader audience than data alone. The latter, natural language query (NLQ), allows individuals to type or speak analytic requests that trigger the delivery of the corresponding data or analysis.

Natural language can enhance business applications, not only by providing conversational interactions for business users but by generating results in natural language so they are easier to understand and act on. In addition, natural language search can make it easier to find and review information and take further actions. These capabilities make completing work simpler and more efficient for every worker in the organization who interacts with business applications, from the front to the back office.

“For many people, a table of numbers or a chart is not as effective as text that explains the meaning of the information and how a person should react to the information,” said David Menninger, SVP & Research Director. “NLP can provide NLG that encompasses narratives that can be used to enhance analytics and applications across business processes, to explain what has happened and why, and even what actions to take.”

This research will identify, explore and quantify key aspects of the future of natural language processing. These aspects include the mandate to improve natural language processing within the organization; how effective it is and why; the challenges of implementation and adoption; and the role of people, processes, information and software in addressing those challenges. The research will investigate what types of organizations are interested in investing in improvements to natural language processing, why they are interested and, with respect to software and technology, who in the organization makes the purchase decisions, on what time frame and using what selection criteria.

Those interested in learning more about or participating in this Dynamic Insights research can click here.

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