What is the core value of large data?

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The core value of large data is the storage and analysis of massive data. Compared with other existing technologies, the overall cost of the "cheap, fast, and optimized" of large data is optimal.

When this technology is in its own use (such as Google, etc.), it will be very profitable, because the cost will be reduced, when the technology in the customer, the customer will also benefit. The technology that enables customers and themselves to benefit at the same time is the most commercially valuable. Therefore, the big data is not just the empty words of shouting slogans, but like other emerging technologies, commercialization is a process, now it seems, large data or belong to the stage of wool, so many people will go to think big data hype suspicion greater.

While large data is not limited to the display of technology, the technology of the Hadoop system is already in fact recognized, so it is not possible to break away from the technology of the Hadoop system while discussing the core value of large data.

  A, massive

This is the key to large data, a small amount of data in the IT industry have many solutions, so large data technology is not an advantage.

Second, storage

Here is the need for a lot of storage technology, the second data storage devices need to be extensible, as long as the storage server nodes increased, the default copy technology to make the data not lost.

Three. Analysis

Massive data analysis must be distributed processing, otherwise the time cost is too large. Distributed technology has long been available, both professional and complex. Hadoop only needs to run dozens of or hundreds of code on distributed processing, and it takes only a short time to complete the basic data analysis on a professional program. Of course, the most professional large data analysis or need experts to complete.

Four. The excellent

Hadoop series technology is specially designed for massive data processing, the top-tier enterprise in IT industry participates in the contribution and the related technology contribution, has the consummation system in the ecology circle, therefore each kind of demand can basically satisfy. Hadoop is superior to the rest of the distributed technology.

Five. Fast

1. Performance on cluster processing will expand linearly with the increase in operational borrowing.

2. Based on the Java language implementation, the threshold of learning is greatly reduced.

3. It is becoming easier to deploy and maintain clusters (there are many automated cluster building and maintenance tools, including many commercial editions, that provide the operational dimension of the Web interface).

6. Cheap

1. There is no need to purchase expensive hardware, software, and services from companies such as IBM, Oracle, EMC, or Windows licensing.

2. Because of the increasing number of people or companies who will have this technology, it is increasingly cheaper to purchase or customize commercial products based on related technologies

in general, the overall cost of large data is optimal relative to other technical systems.