Year: 2025
Type: article
Abstract: This article examines the transformative impact of artificial intelligence and machine learning integration in data engineering. The article explores various dimensions including automated data processing, intelligent pipeline management, advanced data quality monitoring, and smart governance systems. Through multiple case studies and research findings, the article demonstrates how AI-driven solutions have revolutionized traditional data engineering practices, from automated feature engineering in healthcare analytics to enhance security measures in cloud environments. The research highlights significant improvements in processing efficiency, data quality management, and decision-making capabilities across organizations implementing AI-powered systems, while also examining the role of MLOps practices and natural language processing in modernizing data operations.
Author: Gopinath Govindarajan
Institution: University of Madras
Language: English
Topic: Data Quality and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4410061880