Evolution of Data Engineering in Modern Software Development
This discussion summarizes the challenges implicated, including scale and security, outlines strategies for workflow optimization, and elaborates on some findings using data tables and practical code snippets, which brings actionable insights for both practitioners and researchers.
Abstract
Data engineering is ever-evolving and is now increasingly more complex and large-scale in modern applications of software. The paper presents an all-encompassing study about the evolution, core components, technological development, and emerging trends in data engineering largely associated with developing software. Thorough research would also help to know how AI might be integrated into cloud-native architectures, processing frameworks and in data engineering, which should take all real-time data. This discussion summarizes the challenges implicated, including scale and security, outlines strategies for workflow optimization, and elaborates on some findings using data tables and practical code snippets. This brings actionable insights for both practitioners and researchers.