Shulou(Shulou.com)06/03 Report--

Speaking of big data, I guess we all think that we have only heard of the concept, but there is no standard for what it is and how to define it, so I suggest that big data be understood literally. The big data era, written by Victor Scheinberg and Kenneth Kukeye, mentions four features of big data:

1 large quantity

Big data's characteristics are first reflected as "big", from the pre-Map3 era, a small MB-level Map3 can meet the needs of many people, but with the passage of time, the storage unit from the past GB to TB, and even the current PB, EB level. Only when the data volume reaches the PB level or above, can it be called big data. With the rapid development of information technology, data began to grow explosively. Social networks, mobile networks, a variety of intelligent tools, etc., have become the source of data. Nearly 400m members of Taobao generate daily commodity trading data of about 20TB. There is an urgent need for intelligent algorithms, powerful data processing platforms and new data processing technologies to count, analyze, predict and process such large-scale data in real time.

2 high speed

The logical processing speed of the data through the algorithm is very fast, and the law of one second can quickly obtain high-value information from various types of data, which is essentially different from the traditional data mining technology. And these data need to be processed in time, because it is not cost-effective to spend a lot of capital to store less useful historical data. Based on this situation, big data has very strict requirements for processing speed. A large number of resources in the server are used to process and calculate data, and many platforms need to achieve real-time analysis. Data is generated all the time, and whoever is faster will have an advantage.

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3 diversity

If there is only a single data, then the data has no value. A wide range of data sources determine the diversity of big data's forms. Log data is obviously structured data, and some data are not structured obviously, such as pictures, audio, video and so on. The causality of these data is weak, so it needs to be marked manually.

4 value

This is also the core feature of big data. In the data generated in the real world, the proportion of valuable data is very small. If you have online data of more than 20-35 young people across the country with more than 1PB, then it naturally has commercial value. For example, by analyzing these data, we know the hobbies of these people, and then guide the direction of product development, and so on. If we have the data of millions of patients across the country, the analysis based on these data will be able to predict the occurrence of the disease. These are the values of big data. Big data is widely used, such as in agriculture, finance, medical and other fields, so as to improve social governance, improve production efficiency and promote scientific research.

Big data has become the rule of the game in most industries over the past few years, and industry leaders, scholars and other well-known stakeholders agree that as big data continues to work in our daily lives, the hype around big data is turning to real value in practice.

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