Recent Advances in Big Data Analytics and Artificial Intelligence: A Comprehensive Review

The rapid growth of data generated from digital platforms, sensors, and interconnected systems has led to the emergence of Big Data as a critical resource for intelligent decision-making. At the same time, Artificial Intelligence (AI) has evolved significantly, offering powerful techniques to extract meaningful insights from large-scale and complex datasets. This paper presents a comprehensive review of recent advances in Big Data analytics and Artificial Intelligence, focusing on their integration, methodologies, and practical applications. Key Big Data frameworks and analytics paradigms are discussed alongside state-of-the-art AI techniques, including machine learning, deep learning, and natural language processing. The review highlights recent trends such as real-time analytics, scalable AI models, and generative intelligence, while also examining major challenges related to data quality, privacy, scalability, and model interpretability. Furthermore, emerging research directions, including explainable AI, edge–cloud intelligence, and sustainable AI systems, are explored. This review aims to provide researchers and practitioners with a consolidated understanding of current developments and future opportunities at the intersection of Big Data analytics and Artificial Intelligence.