n Intelligent Framework for Big Data Analytics Using Artificial Intelligence and Machine Learning Techniques

Abstract

This paper discusses how big data analytics, artificial intelligence (AI), and machine learning (ML) will be combined to facilitate better decision-making and operational efficiency in many fields including smart cities, business intelligence, and financial technology. The main goal is to study the general contributions of these technologies in the development of scalable, intelligent and data-driven systems. The methodology will be the systemic analysis of current frameworks, algorithms and application models with emphasis on the data processing architecture, predictive modeling techniques and real time analytics. The findings show that big data synergy with AI/ML enhances the pattern recognition, forecasting, and automation abilities considerably, especially with distributed computing systems. Also, the implementation of deep learning and cognitive-spired models strengthens the processing of unstructured and high-dimensional data. It is also emphasized in the study that there are some issues associated with data privacy, computational complexity, and heterogeneous system integration. Finally, the inter-section of big data, AI, and ML offers the opportunities of sustainable development and intelligent system design, but also highlights the necessity to have strong frameworks to tackle scalability, security, and ethical aspects when it comes to future implementations.