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The age of big data is now coming. But the traditional data analytics may not be able to handle such large quantities of data. The question that arises now is, how to develop a high performance platform to efficiently analyze big data and how to design an appropriate mining algorithm to find the useful things from big data.
The problem of handling a vast quantity of data that the system need to process is not a brand-new research issue; in fact, it appeared in several early approaches like marketing analysis, network flow monitor, traffic optimization , and even astronomy analysis.
This problem still exists in big data analytics today; thus, preprocessing is an important task to make the computer, platform, and analysis algorithm be able to handle the input data.
Nowadays, our experience allows us to use the tools and platforms presented by well-known organizations like Amazon or Google. The cloud computing technologies are widely used on these platforms and frameworks to satisfy the large demands of computing power and storage.
Most of the works for big data can be moved to cloud system to speed up the response time or to increase the memory space. With the advance of these works, handling and analyzing big data within a reasonable time has become economical accessible.

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