Big Data Analytics in the Cloud: A Survey of Architectures and Technologies

Abstract

In the contemporary generation of burgeoning records, the combination of Big Data analytics with cloud computing has emerged as a paradigm-transferring pressure, facilitating scalable and efficient processing of big datasets. This review paper gives an intensive survey of architectures and technologies that form the bedrock of Big Data analytics inside cloud environments. Tracing the evolution from conventional records processing to dispensed paradigms, the survey explores key architectures, inclusive of Lambda, Kappa, and serverless, shedding mild on their components and scalability attributes. A specified examination of cloud-primarily based Big Data frameworks together with Apache Hadoop and Apache Spark, together with managed services from principal cloud vendors, gives insights into the various alternatives to be had. The position of cloud-local garage answers, data control techniques, and strategies for scalability and overall performance optimization are dissected. Security and privacy issues in cloud-primarily based Big Data analytics are scrutinized, encompassing encryption mechanisms and compliance frameworks. The evaluate contemplates the challenges inherent inside the area and envisions future
instructions, which includes hybrid cloud architectures and edge computing integration. Industry case studies illustrate practical applications across finance, healthcare, and e-commerce. The end synthesizes key findings, emphasizing the transformative effect of cloud-based totally Big Data analytics on selection-making and innovation. This complete survey serves as a precious resource for researchers, practitioners, and decision-makers navigating the dynamic intersection of Big Data analytics and cloud computing.