arXiv Open Access 2024

Automating Business Intelligence Requirements with Generative AI and Semantic Search

Nimrod Busany Ethan Hadar Hananel Hadad Gil Rosenblum Zofia Maszlanka +2 lainnya
Lihat Sumber

Abstrak

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.

Topik & Kata Kunci

Penulis (7)

N

Nimrod Busany

E

Ethan Hadar

H

Hananel Hadad

G

Gil Rosenblum

Z

Zofia Maszlanka

O

Okhaide Akhigbe

D

Daniel Amyot

Format Sitasi

Busany, N., Hadar, E., Hadad, H., Rosenblum, G., Maszlanka, Z., Akhigbe, O. et al. (2024). Automating Business Intelligence Requirements with Generative AI and Semantic Search. https://arxiv.org/abs/2412.07668

Akses Cepat

Lihat di Sumber
Informasi Jurnal
Tahun Terbit
2024
Bahasa
en
Sumber Database
arXiv
Akses
Open Access ✓