The joy and sorrow in the age of Internet big Data

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Recently, the word "big data" is very hot. With advances in technology and the Internet, data seems to have become an essential tool for changing a business. Especially with the advent of the big data age, some once very difficult problems can be solved. Google, for example, can detect the occurrence and spread of influenza before the public health agencies in the United States, and can even pinpoint a region, with an accuracy rate of up to 97%, which is completely unthinkable in the small data age.

The big Data age has brought great convenience to businesses, governments and individuals alike. The enterprise can accurately judge the customers ' interests and preferences through data analysis, and use this to recommend the most relevant products to customers. The most successful of these is Amazon. Amazon initially used a book review format to recommend books to users, but when it had a lot of user data, it turned to using data analysis to recommend books to users. The turnover rate is much higher than before, and there is no need to comment on editing so it can save a certain amount of manpower cost.

In the big data age, people do not have to struggle to find the causal relationship of things. Only by analyzing the data to get a correlation, that is to say, people need not know the reason why. The Farecast system developed by Eziony, for example, can analyze the number of airline ticket sales data from existing airlines and predict when to buy tickets is the cheapest. But you don't know what makes a ticket cheaper, and that's not the point, people just need to know the result.

In addition, another advance in the big Data age is "sample = All". It is clear that this approach is more accurate than sampling statistics in the small data age. Because the big data age is to analyze all the data as a sample area, to be able to more accurately and promptly discover the details that people have never found, and these details are likely to be related to success or failure. And for these data people no longer blindly pursue precision, but to contain some mixed data. Because this is part of the big data, the more comprehensive the data, the more accurate it will be.

Crucially, the value of large data in business is more important than ever. Data collection and analysis is also becoming cheaper and more convenient than ever before. As long as the enterprise through a large number of customer data analysis can accurately formulate the next business strategy, as well as product improvement. For example, a car company can analyze a customer's sitting data to make a car's anti-theft system, and the bank can analyze your social data to see if you can repay the loan. Although these seem to have little relevance, big data makes it possible.

Although the advent of the big data age has many advantages, there are always two sides to everything. The big Data age brings us a lot of trouble as well as surprises. For example, our personal privacy issues, in the big data age, we will have a "third eye" at all times to stare at our every move. Any of your actions can be an analysis of a business or organization and can be made available to the public at any time. In large data times personal privacy or will become a "pseudo proposition". Once people illegally use, the consequences will be disastrous!

And in the big data age, people's thinking may be hard to change. Therefore, how to correctly analyze and make use of large data becomes an urgent problem to be solved. Although big data can help people predict a trend, such as predicting a possible crime based on a person's past behavior, we cannot convict it based on these predictions. After all, things have not happened, though they can be prevented but cannot be punished.

Finally, in the big data age people tend to rely too much on data analysis. Once the data is wrong, the decisions and judgments made by the data will be wrong. If in the enterprise operation, a wrong data analysis is easy to destroy the enterprise. Moreover, data analysis makes everything more standardized. But that is not entirely true. Some product designs, which require inspiration from designers, require some artistic creation rather than just some cold data. Google is a consummate figure in the use of data, but Google will inevitably make some common sense mistakes. Because Google has chosen a unified performance data standard as the main basis for recruiting talent. However, these are not enough to show whether a person is a talent, but Google stubbornly adhere to this wrong behavior. This is the result of excessive reliance on large data.

As I said, there's always two sides to something. Big data is also creating new problems for humans while helping people solve problems, as well as using large data. Although the big data has strong enough power, but we need to improve is not the size of the database, accurate or not, but our thinking, because thinking is the most fundamental power to harness technology!

This article author Song Congming the original content by Jiangxi Fengcheng Forum: http://www.jxfclt.com collation, A5 initial reprint Please specify, thank you!