
The landscape of data engineering is rapidly evolving, driven by the increasing complexity and volume of data that organizations must manage. Traditional methods, primarily reliant on ETL (extract, transform, and load) processes, are struggling to keep up with the demands of modern data environments. This article explores the potential of large language models (LLMs) to revolutionize data engineering, addressing the