Enterprise processing large data is considered from three dimensions

Source: Internet
Author: User
Keywords Large data three data storage tradition facing

According to IDC, an international data company, published in 2011, Digital Universe Study, the total amount of global information will increase by one times every two years. In 2011 alone, the total amount of data created and replicated globally was 1.8ZB (1.8 trillion GB). Compared with a 2010 increase of more than 1ZB, by 2020 this value will increase to 35ZB.

Social networking is just one part of the 1.8 zeta data, and E-commerce, Enterprise, Internet and personal cloud data storage are also increasing. With the development of the traditional structured data to the unstructured, the data is becoming more and more diverse as the Internet participates in the growth of the people and Internet applications. Video, voice, text, pictures and other traditional single media storage mode has been disrupted, replaced by more interactive data, the contribution of individual users or consumers can not be ignored. At the same time, the development of broadband, wireless communications, cloud computing to make our network faster, access to data readily available, but also to promote greater data prosperity. The number of unstructured data in enterprise management is growing at a geometric level, and the growth rate is accelerating. Considering how to save and use the data reasonably, the pressure on enterprise it is self-evident.

In this connection, the century interconnection Dr. Li Zhijian the Enterprise processing large data can be considered from three dimensions, that is, large data mining, storage, migration.

1. Data Mining

In the cloud, data scattered on different physical machines, Hadoop and other large data mining tools in which the role of pointers, according to the needs of information content to point to the information storage space, forming a data warehouse. The collection of all data warehouses exists in the resource pool in the Cloud data center. Selecting data mining tools based on actual requirements and defining data requirements is the chief task of the CIO.

2. Data storage

When the enterprise data is stored in the cloud or the physical service, it needs the data storage management such as physical location, query, processing and deletion. Every time the data invocation and storage, the enterprise needs to pay the corresponding cost, including power, equipment, bandwidth, computing capacity and so on. Data cloud and IT service outsourcing can reduce the cost of single access, through the data Center energy efficiency, and other ways to help enterprise it reduce overall costs. The upgrade management of the data reading process, such as speed-increasing, redundancy data processing, will maximize the enterprise IT efficiency.

3. Data migration

Cloud migration is a difficult task, requiring specialized tools or service teams. Because there is no interface standard, the user must first select the target cloud. And today's cloud computing a big Short board is the deployment of operational dimension, customer base does not have this ability, and the existing SI also mostly stay in the traditional level of deployment. Therefore, data migration is a major challenge to the future business migration of the enterprise. Selecting a cloud data center service provider with cloud migration capabilities can help enterprises implement transformations from traditional data centers to cloud platforms.

(Responsible editor: The good of the Legacy)

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