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Cloud computing focuses on computing. The purpose is to virtualize physical devices so that users can work remotely anywhere. Big data focuses on data analysis, efficient processing of massive data. Therefore, the two concepts are different and do not conflict with each other.
Cloud computing is an Internet-based computing model. In this mode, shared software and hardware resources and information can be provided to computers and other devices on demand. Cloud is a metaphor for the network and Internet. In the past, the cloud was used to represent the telecommunications network. Later, it was also used to represent the abstraction of the Internet and the underlying infrastructure.
Big data requires special technologies to effectively process a large amount of data that can be processed within a specified period of time. Technologies applicable to big data include massively parallel processing (MPP) databases, data mining grids, distributed file systems, distributed databases, cloud computing platforms, the Internet, and scalable storage systems.
The strategic significance of big data technologies lies not in the control of huge amounts of data but in the professional processing of such meaningful data. In other words, if big data is compared to an industry, the key to making profits in this industry is to improve the data processing capability and add value to data through data processing.
Technically, big data and cloud computing are inseparable from each other. Big data cannot be processed by a single computer. Therefore, a distributed architecture must be used. It features distributed data mining of massive data, but it must rely on distributed processing, distributed database, cloud storage, and virtualization technologies of cloud computing.
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