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.

翻译：商业智能（BI）系统的需求获取在当前快速变化的商业环境中仍是一项重大挑战。本文提出了一种名为AutoBIR的新型人工智能驱动系统，该系统利用语义搜索和大语言模型（LLMs）来自动化并加速BI需求的规范制定。该系统通过对话式界面促进与利益相关者的直观交互，将用户输入转化为原型分析代码、功能描述及数据依赖关系。此外，AutoBIR可生成包含可视化辅助选项的详细测试案例报告，从而简化需求获取流程。通过整合用户反馈，系统能够持续优化BI报表与系统设计，展现了在加速数据驱动决策方面的实际应用价值。本文进一步探讨了生成式人工智能在变革BI开发过程中的广阔潜力，阐明了其在提升大规模演进式系统的数据工程实践中的关键作用。