In this study, we introduce JarviX, a sophisticated data analytics framework. JarviX is designed to employ Large Language Models (LLMs) to facilitate an automated guide and execute high-precision data analyzes on tabular datasets. This framework emphasizes the significance of varying column types, capitalizing on state-of-the-art LLMs to generate concise data insight summaries, propose relevant analysis inquiries, visualize data effectively, and provide comprehensive explanations for results drawn from an extensive data analysis pipeline. Moreover, JarviX incorporates an automated machine learning (AutoML) pipeline for predictive modeling. This integration forms a comprehensive and automated optimization cycle, which proves particularly advantageous for optimizing machine configuration. The efficacy and adaptability of JarviX are substantiated through a series of practical use case studies.

翻译：本研究提出JarviX，一个先进的数据分析框架。JarviX旨在利用大型语言模型（LLM）实现自动化引导，并对表格数据集执行高精度数据分析。该框架强调不同列类型的重要性，借助最先进的LLM生成简洁的数据洞察摘要、提出相关分析问题、有效可视化数据，并为从全面数据分析流程中得出的结果提供详尽的解释。此外，JarviX集成了用于预测建模的自动化机器学习（AutoML）流程。这种集成形成了一个完整且自动化的优化循环，在机器配置优化方面展现出显著优势。通过一系列实际案例研究，验证了JarviX的有效性与适应性。