Advantages and Disadvantages of Automated Data Analysis Driven by Generative AI

DOI

10.2991/978-2-38476-475-4_113How to use a DOI?

Keywords

Generative AI; Automated Data Analysis; Large Language Model; Natural Language Query; Structured Data; Semantic Understanding

Abstract

With the growing demand for data analysis, traditional template- and rule-based automated analysis methods have gradually exposed their limitations in complex query understanding, semantic generalization, and user interaction. In order to solve the problem that the current analysis system is difficult to balance between flexibility and accuracy, this paper proposes an automated data analysis framework based on generative artificial intelligence (GenAI-DA), which integrates task identification, prompt-guided generation, and result feedback mechanisms to build an intelligent analysis system for structured data scenarios. With a large language model as the core, the system combines semantic understanding and structural control strategies to achieve high-quality conversion from natural language input to analysis logic. In multi-task empirical evaluation, the proposed method is superior to existing mainstream methods in terms of accuracy, response efficiency, and user satisfaction, especially in dealing with open-ended task expressions and complex logic construction. It shows stronger robustness and adaptability. The experimental results verify the comprehensive advantages of this system in the three dimensions of automated analysis intelligence, semantic control, and user interaction. The research in this paper not only enriches the application scenarios of generative models in structured tasks, but also provides an effective path and theoretical support for the evolution of data analysis systems to a higher level of intelligence.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Zhuo Chen
PY  - 2025
DA  - 2025/11/11
TI  - Advantages and Disadvantages of Automated Data Analysis Driven by Generative AI
BT  - Proceedings of the 2025 10th International Conference on Modern Management, Education and Social Sciences (MMET 2025)
PB  - Atlantis Press
SP  - 1026
EP  - 1033
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-475-4_113
DO  - 10.2991/978-2-38476-475-4_113
ID  - Chen2025
ER  -