Revolutionizing Database Engineering with Artificial Intelligence

Abstract

Even while database engineering has been expanding at a steady rate, the management and optimization challenges it has always faced are becoming increasingly important as the field moves towards AI. Here, the authors provide more detail on a novel AI-based solution to improve DBS performance, query processing speed, and data security metrics. Adapting to changing patterns and user needs, the suggested framework is improved by a number of methods, such as deep learning, natural language processing, and machine learning algorithms. A forty percent improvement in processing speed and a twenty-five percent improvement in data discovery accuracy were the results of the AI-enhanced database's successful pilot deployment with the top IT corporation. Furthermore, it was shown that vulnerability occurrences were reduced by one for three and a half when AI-based security was used. These outcomes illustrate how AI improves the efficiency and scalability of databases while decreasing the system's vulnerability to faults. Also, the study proves that AI can open up new possibilities for the field of database engineering and greatly improve its current uses.