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. The system facilitates intuitive interaction with stakeholders through a conversational interface, translating user inputs into prototype analytic code, descriptions, and data dependencies. 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:
• 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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