Authors: Khaleel Khan Mohammed
Abstract: Data generation is increasing at an unprecedented pace across industries and the world. The challenge lies not only in storing and managing this massive “big data,” but also in analyzing it to extract meaningful insights. To address this, various methods are employed for data collection, storage, processing, and analysis. This paper provides an overview of the layered architecture of Big Data management and highlights the key challenges within these layers that limit its practical applications across industries. In addition, the study explores different cloud-based architectural models that are designed to support diverse industrial requirements, emphasizing their role in enhancing scalability, flexibility, and efficiency. Furthermore, the paper discusses data migration strategies in detail, outlining how these approaches address the inherent limitations of Big Data systems by enabling seamless transfer, integration, and optimization of data in cloud environments
DOI: http://doi.org/10.5281/zenodo.17339856
