Loading...
B. Lakshmi Roopa is an Assistant Professor in the Department of Computer Science and Business Systems at Jerusalem College of Engineering, India. Her contribution focuses on AI-enhanced analytics, cloud technologies, and Big Data applications.
The swift production of data from social media, Internet of Things (IoT) devices, corporate applications, sensors, mobile devices, healthcare systems, financial platforms, and industrial infrastructure has engendered a substantial need for scalable data-processing technology. Conventional data-processing systems frequently encounter difficulties with the magnitude, speed, diversity, and intricacy of contemporary datasets. Big Data Analytics tackles these issues by offering distributed methodologies for the collection, storage, processing, analysis, and visualisation of extensive datasets. The amalgamation of Artificial Intelligence (AI) with cloud computing significantly augments Big Data Analytics by facilitating intelligent forecasting, categorisation, anomaly identification, automated decision processes, and instantaneous analytics. Cloud platforms offer scalable computing, decentralised storage, virtualisation, and resources available on demand, whereas AI algorithms convert extensive datasets into practical insights. This chapter examines the principles of Big Data, cloud architectures, AI-enhanced analytics, data processing systems, machine learning, deep learning, real-time data analysis, data security, applications, problems, performance indicators, and prospective research avenues.