TiInsight: A SQL-based Automated Exploratory Data Analysis System through Large Language Models
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arXiv
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| Auteurs principaux: | , , , , , , , , , , , , |
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| Format: | Preprint |
| Publié: |
2026
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| _version_ | 1866913058750726144 |
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| author | Zhu, Jun-Peng Niu, Boyan Cai, Peng Ni, Zheming Xu, Kai Huang, Jiajun Ma, Shengbo Wang, Bing Zhou, Xuan Bao, Guanglei Zhang, Donghui Tang, Liu Liu, Qi |
| author_facet | Zhu, Jun-Peng Niu, Boyan Cai, Peng Ni, Zheming Xu, Kai Huang, Jiajun Ma, Shengbo Wang, Bing Zhou, Xuan Bao, Guanglei Zhang, Donghui Tang, Liu Liu, Qi |
| contents | The SQL-based exploratory data analysis has garnered significant attention within the data analysis community. The emergence of large language models (LLMs) has facilitated the paradigm shift from manual to automated data exploration. However, existing methods generally lack the ability for cross-domain analysis, and the exploration of LLMs capabilities remains insufficient. This paper presents TiInsight, an SQL-based automated cross-domain exploratory data analysis system. First, TiInsight offers a user-friendly GUI enabling users to explore data using natural language queries. Second, TiInsight offers a robust cross-domain exploratory data analysis pipeline: hierarchical data context (i.e., HDC) generation, question clarification and decomposition, text-to-SQL (i.e., TiSQL), and data visualization (i.e., TiChart). Third, we have implemented and deployed TiInsight in the production environment of PingCAP and demonstrated its capabilities using representative datasets. The demo video is available at https://youtu.be/JzYFyYd-emI. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_09404 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | TiInsight: A SQL-based Automated Exploratory Data Analysis System through Large Language Models Zhu, Jun-Peng Niu, Boyan Cai, Peng Ni, Zheming Xu, Kai Huang, Jiajun Ma, Shengbo Wang, Bing Zhou, Xuan Bao, Guanglei Zhang, Donghui Tang, Liu Liu, Qi Databases Human-Computer Interaction H.4 The SQL-based exploratory data analysis has garnered significant attention within the data analysis community. The emergence of large language models (LLMs) has facilitated the paradigm shift from manual to automated data exploration. However, existing methods generally lack the ability for cross-domain analysis, and the exploration of LLMs capabilities remains insufficient. This paper presents TiInsight, an SQL-based automated cross-domain exploratory data analysis system. First, TiInsight offers a user-friendly GUI enabling users to explore data using natural language queries. Second, TiInsight offers a robust cross-domain exploratory data analysis pipeline: hierarchical data context (i.e., HDC) generation, question clarification and decomposition, text-to-SQL (i.e., TiSQL), and data visualization (i.e., TiChart). Third, we have implemented and deployed TiInsight in the production environment of PingCAP and demonstrated its capabilities using representative datasets. The demo video is available at https://youtu.be/JzYFyYd-emI. |
| title | TiInsight: A SQL-based Automated Exploratory Data Analysis System through Large Language Models |
| topic | Databases Human-Computer Interaction H.4 |
| url | https://arxiv.org/abs/2601.09404 |