Real-Time Data Processing in AI-Powered ETL: Innovations and Practical Applications

Abstract

The advent of big data and the increasing demand for timely insights have propelled the evolution of Extract, Transform, Load (ETL) processes into real-time data processing frameworks powered by artificial intelligence (AI). This paper explores the innovations in AI-powered ETL systems, focusing on their architecture, key technologies, and practical applications across various industries. By examining case studies, we highlight the transformative impact of real-time data processing on decision-making and operational efficiency.