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What are the differences between CVM and big data? Many novices are not very clear about this. In order to help you solve this problem, the following editor will explain it in detail. People with this need can come and learn. I hope you can gain something.

Cloud server is a product based on cloud computing technology platform, many enterprises will carry out data mining, but if they can not obtain the data value at the lowest cost, the enterprise will not be able to survive. The tool to turn data into wealth at low cost is cloud computing.

Technically speaking, the relationship between big data and cloud computing and the pros and cons are inseparable. Big data can not be processed by a computer, it must be a distributed computing structure. Let's introduce the relationship between cloud computing and big data.

Cloud computing is a prerequisite for extracting big data.

In the information society, the amount of data is increasing and the technical level is constantly improving. Most enterprises can get extra income from big data. Under the premise of massive data, if the cost of extracting, processing and using the data exceeds the value of the data itself, the value is equal to no value. Powerful cloud computing server capabilities from public, private, and hybrid clouds are critical to reducing the cost of data extraction.

Cloud computing servers filter useless information

In general, 90% of the data collected for the first time is useless, so it is necessary to filter it out. In a large amount of useless data, it is important to filter out two kinds of data, one is to store a large amount of temporary information, and the other is the network data from the outside of the company firewall to the internal network, which is of low value. CVM can provide extended computing and storage resources as needed, and can be used to filter useless data. The public cloud is the best choice for handling network data outside the firewall.

Cloud computing servers effectively analyze data

In the data analysis phase, cloud computing service providers can introduce public cloud and hybrid cloud technologies. In addition, the distributed processing software platform can also be used in the stage of centralized data processing. When analyzing data, the original data provided for analysis does not need to be saved at any time. Private cloud can be used to process the analysis results, and information can be imported into the internal information of the company.

CVM helps enterprises manage virtualization

Use existing information to guide decision-making. By applying the software as a service to the cloud platform, we can transform the existing information into the existing enterprise system and help enterprises to strengthen the management model. At present, more and more enterprises realize that cloud computing will make big data's analysis easier in the future. If we can further explore the combination of big data and cloud computing, it will make enterprises more competitive in the global market.

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