Empowering Non-Technical Users: A Chatbot-Driven Approach to Database Management

Modern enterprise applications must provide efficient and user-friendly access to databases, even for users with limited technical expertise. Traditional database management often requires advanced SQL knowledge, creating dependencies on specialized personnel and increasing operational bottlenecks. To bridge this gap, the integration of natural language processing (NLP) models in database management introduces a new paradigm, allowing users to interact with databases conversationally. This paper explores the impact of AI-powered chatbots on database accessibility, focusing on a case study that utilizes a natural language model to generate SQL queries. By analyzing the benefits and limitations of this approach, the study highlights key advantages such as improved productivity, reduced reliance on IT teams, and enhanced error handling. The chatbot-driven system is evaluated in comparison to traditional SQL-driven workflows, demonstrating its potential to streamline data access while maintaining security and reliability.

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Publication Details

Published
2025-05-29
DOI
https://doi.org/10.1109/emes65692.2025.11045570
Primary Topic
AI in Service Interactions
Type
article
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article

Empowering Non-Technical Users: A Chatbot-Driven Approach to Database Management

Cornelia Győrödi, Robert Győrödi, Adelin Gruian
AI in Service Interactions
article

Empowering Non-Technical Users: A Chatbot-Driven Approach to Database Management

Cornelia Győrödi, Robert Győrödi, Adelin Gruian
article en

Abstract

Modern enterprise applications must provide efficient and user-friendly access to databases, even for users with limited technical expertise. Traditional database management often requires advanced SQL knowledge, creating dependencies on specialized personnel and increasing operational bottlenecks. To bridge this gap, the integration of natural language processing (NLP) models in database management introduces a new paradigm, allowing users to interact with databases conversationally. This paper explores the impact of AI-powered chatbots on database accessibility, focusing on a case study that utilizes a natural language model to generate SQL queries. By analyzing the benefits and limitations of this approach, the study highlights key advantages such as improved productivity, reduced reliance on IT teams, and enhanced error handling. The chatbot-driven system is evaluated in comparison to traditional SQL-driven workflows, demonstrating its potential to streamline data access while maintaining security and reliability.

University of Oradea (RO)
Openalex Percentile: Top 93%
AI in Service Interactions
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