Indian Institute of Technology (Indian School of Mines), India.
World Journal of Advanced Engineering Technology and Sciences, 2025, 15(01), 1604-1615
Article DOI: 10.30574/wjaets.2025.15.1.0365
Received on 08 March 2025; revised on 17 April 2025; accepted on 19 April 2025
The advent of artificial intelligence is transforming business intelligence, reshaping the roles of data professionals, and offering unprecedented capabilities across the data lifecycle. This article examines how AI technologies are revolutionizing data engineering through automated pipeline construction, intelligent data quality management, and seamless data integration while simultaneously enhancing data science with automated feature engineering, democratized machine learning, and explainable decision support. Current trends in real-time analytics, cloud-native architectures, edge intelligence, and federated learning illustrate the evolving landscape. Despite these advancements, significant challenges persist in data governance, algorithmic bias, model explainability, and workforce transformation. By exploring both opportunities and limitations, the article provides a balanced perspective on how organizations can harness AI to elevate their business intelligence capabilities while addressing ethical and practical concerns.
Artificial Intelligence; Business Intelligence; Data Engineering; Automated Machine Learning; Responsible Ai; Data Science
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Ankit Pathak. The transformative impact of AI on data engineering, data science, and business
intelligence. World Journal of Advanced Engineering Technology and Sciences, 2025, 15(01), 1604-1615. Article DOI: https://doi.org/10.30574/wjaets.2025.15.1.0365.