Research on an Automated Data Insight Generation Method Based on Large Language Models

Jingtao Hong; Huichen Ma

doi:10.70393/6a69656173.333436

OPEN ACCESS |Research Article ||3 December 2025

Research on an Automated Data Insight Generation Method Based on Large Language Models

Jingtao Hong

Columbia University

jhong711785364@gmail.com

Columbia University, Richmond, VA, USA.

Huichen Ma

University of California San Diego

huma@ucsd.edu

Master of Science in Computer Science, University of California San Diego, Department of Computer Science and Engineering, Jacobs School of Engineering 9500 Gilman Dr, La Jolla, CA 92093, USA.

* Corresponding Author¹: Jingtao Hong, E-Mail: jhong711785364@gmail.com

* Corresponding Author²: Huichen Ma, E-Mail: huma@ucsd.edu

Publication

Accepted 2025 November 28 ; Published 2025 December 3

Journal of Industrial Engineering and Applied Science, 2025, 3(6), 3005-6071.

Abstract

This study aims to explore automated data insight generation methods based on large language models (LLMs), and systematically analyzes the application potential and challenges of LLMs in the field of data insights. Starting from an overview of LLMs and their development, it expounds the theoretical foundations and technological evolution of LLMs in natural language processing. Then, the research method and experimental scheme are elaborately designed, and empirical studies are conducted using deep learning frameworks and large-scale datasets. Experimental results show that automated data insight generation methods based on LLMs exhibit significant advantages in data understanding, pattern recognition, and information extraction, effectively improving the accuracy and efficiency of data insights. Through multi-dimensional analysis of the experimental results, the study reveals the unique advantages and limitations of this method in handling complex data structures and high-dimensional data. Furthermore, the study discusses the theoretical mechanisms and technical bottlenecks behind the results, and proposes concrete strategies for optimizing model performance and expanding application scenarios. Finally, this paper summarizes the research findings and looks ahead to future research directions, with the aim of providing theoretical support and technical references for the further development of automated data insight generation.

Keywords

Large Language Models , Automated Data Insights , Deep Learning , Natural Language Processing , Data Mining , Machine Learning .

Metadata

DOI:

10.70393/6a69656173.333436

ARK:

ark:/40704/JIEAS.v3n6a02

Pages: 6-12

References: 18

Disciplines: Artificial Intelligence Technology

Subjects: Natural Language Processing

Cite This Article

APA Style

Hong, J. & Ma, H. (2025). Research on an automated data insight generation method based on large language models. Journal of Industrial Engineering and Applied Science, 3(6), 6-12. https://doi.org/10.70393/6a69656173.333436

Acknowledgments

The authors thank the editor and anonymous reviewers for their helpful comments and valuable suggestions.

FUNDING

Not applicable.

INSTITUTIONAL REVIEW BOARD STATEMENT

Not applicable.

DATA AVAILABILITY STATEMENT

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

INFORMED CONSENT STATEMENT

Not applicable.

CONFLICT OF INTEREST

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

AUTHOR CONTRIBUTIONS

Not applicable.

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