On February 25, 2021, Naver shut down its portal's real-time search chart service. This happened because big data, the amount of searches that individuals have made, was being used for political and commercial purposes. Do you know about big data? Most of you may have heard of the term, but you may not know its exact definition. Big data refers to a large amount of data that is difficult to collect, store, and analyze with existing databases. In the era of the Fourth Industrial Revolution, where Internet of Things usage has soared, data is continuously accumulating behind the scenes. Smartphones are a good representative of this phenomenon. They leave traces of even a casual search, and these marks are collected as data. These sets of data are reused for many purposes and become meaningful information. It can be used commercially and it is also in close contact with everyday life. Then how does each data become meaningful information?
Chapter 1: Election Prediction Using Big Data
Voting is called the flower of democracy. Would you believe that big data is also used in presidential elections? During the 2016 U.S. presidential election, the author mentions that the media and other corporations had to suddenly prepare for Trump's election after they all predicted Hillary Clinton's election. His argument was "the amount of searches related to Trump is higher than that related to Hillary". Then how does the amount of search relate to the turnout? The author starts with the assumption, "Considering that you generally search for candidates you are more interested in, we can consider having a lot of searches a high percentage of likes." Eventually, the winner of the presidential election turned out to be Trump, and the author became a star in one day. He had neither the superpower to preview all voters' votes nor the power to analyze them based on huge assets, but he did have the ability to analyze data. There is nothing special about the data he used. It was just Google Trend, which anyone can get if they have access to the Internet.
Chapter 2: Predicting a firm's sales and stock prices using big data
The author also uses the same analysis method to predict Britain's Brexit voting results and also forecast companies' future sales and stock prices. The process cited in the text was as follows. It starts with the assumption that when interest in a company or product arises, it will lead to an online search of the company and an increase in the probability of purchasing products from the company. After this, he proves a structure in which the company's sales and stock prices increase gradually.
Eventually, the tiny parts of judging are different. But the basic methods and attitudes are the same: the quantity of search, in other words, big data. The author emphasizes the process for data, which would have been considered a meaningless waste, to be created with new results, and emphasizes that big data is not an option but a necessity in the future.
In modern society, individuals create many traces without knowing about them. The details of the credit cards we use, mobile phone location information, and even Kakao Talk conversations are all quantified. All of this is big data. The basis of such a rapid increase in big data is the development of accumulation systems based on the development of IT technology. Things that were not previously thought to be data are accumulated in vast quantities based on the development of technology and began to be known in the world through analysis by experts. As the author said, this is only the beginning. Why don't you learn about big data now to prepare for the upcoming tsunami of information?
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