Revolutionizing Database Engineering with Artificial Intelligence

Abstract

While database engineering has grown continuously over the years, its management and optimization issues are proving highly relevant as Database Engineering migrates to Artificial Intelligence (AI). Here, the authors elaborate on an original AI-based proposal intended to enhance the performance of DBS and the speed of the queries' processing while strengthening the security measures applied to the data. The proposed framework is enhanced by various techniques, including machine learning algorithms, natural language processing, and deep learning techniques that dynamically evolve to new patterns and new user requirements. The pilot implementation with the leading tech company shows the effectiveness of the AI-enhanced database with an increase in the processing speed of 40% and better accuracy in finding the data by 25%. Furthermore, it was found that using AI-based security lowered vulnerability incidents by one for three and a half. These results describe how AI enhances database scalability and efficacy and reduces the susceptibility of a system to failures. At the same time, the study establishes that AI can substantially enrich the practice of database engineering for contemporary applications and pave the way for further development dimensions of the field.