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arXiv · 2412.07668

Automating Business Intelligence Requirements with Generative AI and Semantic Search

Nimrod Busany·Ethan Hadar·Hananel Hadad·Gil Rosenblum·Zofia Maszlanka·Okhaide Akhigbe·Daniel Amyot
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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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Nimrod Busany, Ethan Hadar, Hananel Hadad, Gil Rosenblum, Zofia Maszlanka, Okhaide Akhigbe, Daniel Amyot. 2024-12-10. Automating Business Intelligence Requirements with Generative AI and Semantic Search. https://arxiv.org/abs/2412.07668

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