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    <abstract>Exploring data is crucial in data analysis, as it helps users understand and interpret the data more effectively. However, performing effective data exploration requires in-depth knowledge of the dataset, the user intent and expertise in data analysis techniques. Not being familiar with either can create obstacles that make the process time-consuming and overwhelming. To address this issue, we introduce InsightPilot, an LLM (Large Language Model)-based, automated data exploration system designed to simplify the data exploration process. InsightPilot features a set of carefully designed analysis actions that streamline the data exploration process. Given a natural language question, InsightPilot collaborates with the LLM to issue a sequence of analysis actions, explore the data and generate insights. We demonstrate the effectiveness of InsightPilot in a user study and a case study, showing how it can help users gain valuable insights from their datasets.</abstract>
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%0 Conference Proceedings
%T InsightPilot: An LLM-Empowered Automated Data Exploration System
%A Ma, Pingchuan
%A Ding, Rui
%A Wang, Shuai
%A Han, Shi
%A Zhang, Dongmei
%Y Feng, Yansong
%Y Lefever, Els
%S Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
%D 2023
%8 December
%I Association for Computational Linguistics
%C Singapore
%F ma-etal-2023-insightpilot
%X Exploring data is crucial in data analysis, as it helps users understand and interpret the data more effectively. However, performing effective data exploration requires in-depth knowledge of the dataset, the user intent and expertise in data analysis techniques. Not being familiar with either can create obstacles that make the process time-consuming and overwhelming. To address this issue, we introduce InsightPilot, an LLM (Large Language Model)-based, automated data exploration system designed to simplify the data exploration process. InsightPilot features a set of carefully designed analysis actions that streamline the data exploration process. Given a natural language question, InsightPilot collaborates with the LLM to issue a sequence of analysis actions, explore the data and generate insights. We demonstrate the effectiveness of InsightPilot in a user study and a case study, showing how it can help users gain valuable insights from their datasets.
%R 10.18653/v1/2023.emnlp-demo.31
%U https://aclanthology.org/2023.emnlp-demo.31
%U https://doi.org/10.18653/v1/2023.emnlp-demo.31
%P 346-352

Markdown (Informal)

[InsightPilot: An LLM-Empowered Automated Data Exploration System](https://aclanthology.org/2023.emnlp-demo.31) (Ma et al., EMNLP 2023)

• InsightPilot: An LLM-Empowered Automated Data Exploration System (Ma et al., EMNLP 2023)

ACL

• Pingchuan Ma, Rui Ding, Shuai Wang, Shi Han, and Dongmei Zhang. 2023. InsightPilot: An LLM-Empowered Automated Data Exploration System. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pages 346–352, Singapore. Association for Computational Linguistics.