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

In fact, the origin of big data's concept is very closely related to time, on the one hand, the type and amount of data per unit time, and on the other hand, the accumulation of data in historical time. The cross-compound growth of these two aspects makes the data possible to be called large.

From ancient times to the present, human individuals have created the same amount of data per unit time, but there are great internal differences.

The first difference can be called the difference in data quality. In the past, people did very few kinds of things per unit time, so it was easy to do classification and aggregation. Modern people switch tasks too frequently, so they need more data to describe them. Regardless of the quality of work, we can say that the previous data is single and the quality is poor, but now the data is rich and the quality is good.

The second difference involves the concept of usability, including accessibility, processability, and whether the results are meaningful or not. We say that the availability of the previous data is poor. The biggest reason is the lack of collection methods and no effective means to obtain data. Another important reason is the convergence of data generated by a large number of individuals, heroes create the trend, and there are few heroes, so a large number of studies on history tend to count the data of groups rather than individuals.

But there are great differences in modern society. The richness of material and the colorful spirit make human individuals have more choices about how to live. The masses of the people make the times, the times make heroes, and everyone is a hero. Think of ourselves as producers of data, and more choices in life actually produce more kinds of data. In the past, there were thousands of people, but now it is possible to have a thousand people. The development of human society is essentially a process of entropy increase.

An important difference between people and animals is that people can make and use tools. Modern people have enough tools to do more in less time than our ancestors. This statement sounds too seductive, from the limit, human beings can do unlimited things in a limited time, although our feeling is that modern people are running out of time. Then, in turn, for data, they have more and more time for us, which is also infinite. From this point of view, it is not that we have the data, but that the data owns us.

If we go further, we should think that one direction of big data's development could be "personal big data", that is, the purpose of this application is to create his own database and analysis system for an individual. Because the amount of data of a single person is so large that it can be called big data.

At present, if you want to get a person's data, the most fundamental thing is to control his time. The most precious thing for a person is his time. A variety of APP applications are essentially data collectors, and the first task is to attract people to immerse themselves in them, because the amount of data depends on how much time people spend on an application.

However, when an application takes up too much of people's time, the situation changes. An obvious example is that all kinds of applications that claim to be accurate push often recommend something that users don't want, or it is the application that "nurtures" users, which is not the case. Then the data of this kind of butt determines the head and its analysis is obviously not accurate.

Big data is our tool to assist decision-making and save decision-making time. On the one hand, through the development and upgrading of big data system components and faster and faster hardware, this so-called tool tool. On the one hand, big data's application, search, e-commerce, finance, medical care, and even all aspects of life.

Although there is a lot of data, it can be processed quickly, saving people's thinking time. The ability to think is the only difference between the living and the dead. In 2015, humans created a total of 4.4 billion TB of 4.4ZB data, and that number doubles about every two years, but less than 10% of the data is analyzed each year. Do people spend more time collecting and processing data in order to save time in decision-making? Will the so-called "resource curse" appear in big data's field?

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