Data exploration with a conversational user interface (UI) represents one of the most innovative applications of LLMs in BI.
With natural language query processing, LLMs can understand and process queries made in natural language, allowing users to ask questions about their data as they would in a conversation. For example, a user might ask, “What were the total sales last quarter by region?” and the LLM can interpret this query, fetch the relevant data, and present it in an understandable format.
“The power of the large language model engine allows people poland whatsapp number data to talk in very plain, vernacular type language and get a response in the same tone and feeling. And that’s what makes the LLM chatbot so interesting,” explains Avi Perez.
“The integration into business intelligence, or BI, is then very appropriate because, typically, people have a lot of questions around the data that they’re looking at and would like to get answers about it,” he continues. “Just a simple, ‘Show me my numbers,’ all the way through to the more interesting aspect which is the analysis. ‘Why is this number what it is? What will it be tomorrow? What can I do about it?’ So on and so forth. So it’s a very natural fit between the two different sets of technologies.”
Moreover, conversational UIs powered by LLMs can offer dynamic interactions, where the system asks follow-up questions to clarify the user’s intent or to drill down into more specific details. LLMs are capable of maintaining context over the course of a conversation. This interaction mimics a dialogue with a human analyst, making the exploration process more engaging and thorough.