Automating Business Intelligence Requirements with Generative AI and Semantic Search
December 10, 2024 Β· Declared Dead Β· π Annual International Computer Software and Applications Conference
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Authors
Nimrod Busany, Ethan Hadar, Hananel Hadad, Gil Rosenblum, Zofia Maszlanka, Okhaide Akhigbe, Daniel Amyot
arXiv ID
2412.07668
Category
cs.SE: Software Engineering
Citations
2
Venue
Annual International Computer Software and Applications Conference
Last Checked
4 months ago
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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