Automating Business Intelligence Requirements with Generative AI and Semantic Search

• URL: http://arxiv.org/abs/2412.07668v1
• Date: Tue, 10 Dec 2024 16:57:48 GMT
• Title: Automating Business Intelligence Requirements with Generative AI and Semantic Search
• Authors: Nimrod Busany, Ethan Hadar, Hananel Hadad, Gil Rosenblum, Zofia Maszlanka, Okhaide Akhigbe, Daniel Amyot,
• Abstract summary: This paper introduces a novel AI-driven system, called AutoBIR, to automate and accelerate the specification of Business Intelligence (BI) requirements.<n>The system facilitates intuitive interaction with stakeholders through a conversational interface, translating user inputs into prototype analytic code, descriptions, and data dependencies.<n>By incorporating user feedback, the system refines BI reporting and system design, demonstrating practical applications for expediting data-driven decision-making.
• Score: 0.5193262058345202
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Eliciting requirements for Business Intelligence (BI) systems remains a significant challenge, particularly in changing business environments. This paper introduces a novel AI-driven system, called AutoBIR, that leverages semantic search and Large Language Models (LLMs) to automate and accelerate the specification of BI requirements. The system facilitates intuitive interaction with stakeholders through a conversational interface, translating user inputs into prototype analytic code, descriptions, and data dependencies. Additionally, AutoBIR produces detailed test-case reports, optionally enhanced with visual aids, streamlining the requirement elicitation process. By incorporating user feedback, the system refines BI reporting and system design, demonstrating practical applications for expediting data-driven decision-making. This paper explores the broader potential of generative AI in transforming BI development, illustrating its role in enhancing data engineering practice for large-scale, evolving systems.

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