Big data as the need for new processing models to have stronger decision-making power, insight discovery and process optimization capabilities to adapt to the massive, high growth rate and diverse information assets. Big data is also a large scale in terms of access, storage, management, analysis of data collections beyond the scope of the capabilities of traditional database software tools, with massive data scale, rapid data flow, diverse data types and low value density of the four characteristics. The strategic significance of big data technology does not lie in the mastery of huge data information, but in these data containing the meaning of specialized processing.

In other words, if big data is compared to an industry, the key to the profitability of this industry lies in the improvement of the "processing capacity" of the data, and the "value-addedness" of the data is realized through "processing". The key to the profitability of this industry lies in improving the "processing capability" of data and realizing the "value-added" of data through "processing". From a technical point of view, the relationship between big data and cloud computing is like the positive and negative sides of a coin as inseparable. Big data inevitably can not be processed by a single computer, must be distributed architecture. It is characterized by distributed data mining of massive amounts of data. But it must rely on cloud computing's distributed processing, distributed database and cloud storage, and virtualization technologies.

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