Machine Learning and AI in Data Analytics: A State-of-the-Art Review

Abstract

This review discusses the technological revolution of Machine Learning and Artificial Intelligence in data analytics, its origins, key ideas, methods, uses, tools, issues, and trends. It describes the process of converting the conventional descriptive analytics to intelligent, predictive, and automated analytics powered by the big data, cloud computing, and advanced algorithms. The most important ML methods, including regression, classification, clustering, and deep learning, and the latest models, like ensemble methods and transformers, are elaborated. Its applications are in the fields of healthcare, finance, business intelligence, and cybersecurity. Nevertheless, AI-driven analytics is improving despite such obstacles as bias, scalability, and privacy issues, with the help of AutoML, edge computing, and generative AI, and it is the future of intelligent decision-making.