ARTIFICIAL INTELLIGENCE IN DATA INTEGRATION: ADDRESSING SCALABILITY, SECURITY, AND REAL-TIME PROCESSING CHALLENGES

This article examines the pivotal role of Artificial Intelligence (AI) in addressing data integration challenges faced by large enterprises. As organizations grapple with an ever-increasing volume and diversity of data sources, AI and Machine Learning (ML) technologies are emerging as critical solutions for efficient data management. The article explores three primary forms of data integration—consolidation, virtualization, and propagation—and their significance in contemporary data environments. It analyzes how AI techniques are revolutionizing data mapping, quality enhancement, and real-time processing, thereby mitigating key issues such as data silos, incompatibility, and scalability concerns. Through a series of case studies, the article demonstrates AI's transformative impact on data integration practices across various industries. The article further investigates how AI-driven data integration is reshaping strategic decision-making processes and operational efficiencies in enterprises. By synthesizing current developments and future trends, this article provides valuable insights for data professionals and business leaders seeking to leverage AI for improved data integration and management strategies.