BIG DATA AND CLOUD COMPUTING

Abstract

Big Data may be a data analysis methodology enabled by recent advances in technologies and architecture. However, big data leads to enormous commitment of hardware and processing resources, which prevents the adoption costs of massive data technology for small and medium-sized businesses.Cloud computing offers the promise of massive data implementation to small and medium sized businesses.Big processing is performed through a programming paradigm referred to as MapReduce. Typically, implementation of the MapReduce paradigm requires networked attached storage and multiprocessing . The computing needs of MapReduce programming are often beyond what small and medium sized business are ready to commit. Cloud computing is on-demand network access to computing resources, provided by an outdoor entity. Common deployment models for cloud computing include platform as a service (PaaS), software as a service (SaaS), infrastructure as a service (IaaS), and hardware as a service (HaaS). The three sorts of cloud computing are the general public cloud, the private cloud, and therefore the hybrid cloud. A public cloud is that the pay- as-you-go services. a personal cloud is internal data center of a business not available to the overall public but supported cloud structure. The hybrid cloud may be a combination of the general public cloud and personal cloud. Three major reasons for little to medium sized businesses to use cloud computing for giant data technology implementation are hardware cost reduction, processing cost reduction, and skill to check the worth of massive data. the main concerns regarding cloud computing are security and loss ofcontrol.