Integrating NLP into your database can revolutionize the way your business utilizes language data.
There has been a lot of excitement surrounding Natural Language Processing (NLP), partially due to the success of language generation tools like ChatGPT, a model that can produce creative and coherent text. However, NLP can also be used to achieve the opposite – converting everyday language into structured data, adding business-oriented dimensions such as emotions, topics, and action items. It’s important to take a step back and consider the potential business value that these developments can bring.
Language understanding at scale
With the vast amount of language data at our disposal, the ability to extract insights from this unstructured data is more crucial than ever before. The potential of language has long been acknowledged, but until recently, understanding language at scale and at a high quality has remained an elusive task. Additionally, the cost of entry to utilize this technology has been a barrier for most organizations. However, recent advancements in technology have made it possible to create advanced NLP that is both accurate and affordable. This breakthrough is opening up new possibilities for businesses and organizations to unlock value and insights from their language data, and drive innovation.
See also: OpenAI Launches AI Dialogue Model ChatGPT
Natural Language Understanding-based dimensions in your database
Imagine adding columns to your database that not only store traditional data but also contain information extracted from natural language text. These new columns could include “mentioned people,” “places,” or even more specifically, “airports,” “laws,” or “regulations.” You could also use language understanding to automatically convert everyday language into structured data types, such as date & time values, pricing, and interest rates, which were previously challenging to extract from unstructured text.
With this integrated into your database, you would be able to gain a deeper understanding of your business and make more informed decisions. For example, you could see which individuals are most frequently mentioned negatively in customer interactions or which locations are most associated with a particular product or service. This information can be used to improve customer interactions and personalize the customer experience. You could also see which emotions are most prevalent in customer interactions and use this information to improve customer service or develop new products or services.
Business impact
NLP can be used to quickly and accurately digest massive amounts of language data. By integrating NLP capabilities at the core of the company’s operations, at the database layer, rather than just at the surface-level application layer, an almost endless array of fundamental and essential use cases become readily available. Organizations can gain insights and make informed decisions not just on the analytical level but also on the operational and customer experience levels. It allows for more accurate and efficient searching and retrieval of data, improved sentiment analysis, and even personalization of customer interactions. This can lead to a better understanding of customer needs and preferences, which can, in turn, drive better decision-making and improve the overall customer experience. Additionally, it provides the ability to automate repetitive tasks, such as data entry and data categorization, which can result in cost savings and improved efficiency. Another benefit of using NLP in your database is the ability to power your search functionality with content and intent comprehension capabilities. You can improve the accuracy and relevance of search results, making it easier for users to find the information they need. The possibilities are endless when it comes to the potential benefits of adding NLP to the database layer.
Integrating NLP into your database can revolutionize the way your business utilizes language data.
