Big Data using Cloud Computing: Security Issues and Approaches

Abstract

Big Data is a data analysis methodology made possible by current technological and architectural advancements. However, big data requires a significant investment in hardware and processing power, making it prohibitively expensive for small and medium-sized firms to implement. Small and medium-sized enterprises can benefit from cloud computing promise of big data implementation. The MapReduce programming paradigm is used to process large amounts of data. The MapReduce paradigm typically necessitates networked connected storage and parallel computation. The computing requirements of MapReduce programming are frequently beyond the capabilities of small and medium-sized businesses. Cloud computing is network access to computing resources on demand, given by a third party Hardware cost reduction, processing cost reduction, and the flexibility to verify the value of big data are three significant reasons for small and medium-sized organizations to embrace cloud computing for big data technology implementation. Security and loss of control are two main concerns with cloud computing. Key Words: Big data, MapReduce, cloud computing, private cloud, public cloud, and hybrid cloud.