After Zhou Fangyuan left the hotel, he asked the driver to take him to the second uncle's house.

When he arrived at the second uncle's house, the second uncle and the second aunt were still arguing, and when they saw him coming, the two immediately stopped.

Zhou Fangyuan didn't talk nonsense, explained his intention straightforwardly, and said that he had already found a channel for Huihui to study abroad.

The second aunt couldn't help but feel a little ashamed when she heard this, after all, it was because of her noise that Huihui called Zhou Fangyuan, and then Zhou Fangyuan helped them contact the school, which made her feel as if she was in a hurry to force Zhou Fangyuan to do this. Although this is the case, when she faced Zhou Fangyuan in person, she still felt a little embarrassed.

"Don't be embarrassed, second aunt, Huihui is my sister, since I have this ability, I must help. But before that's done, I'm going to explain some of the issues to you......"

Immediately afterwards, he talked about the advantages and disadvantages of studying abroad, as well as the problems he may face in the future.

Some of them were thought of by the second uncle, and some were not expected by them, Zhou Fangyuan could not take care of Huihui anytime and anywhere, she would face a lot of problems when she went abroad as a girl, and some of the problems were still very important, and it was not difficult to destroy a person directly if one did not do it well, so the second uncle and the second aunt must know it.

……

After taking care of Huihui's affairs, the next day, Zhou Fangyuan came to the remote information processing company in the western suburbs of Beitong City, which was the big data center he prepared for the future.

Big data, this is a word that has almost been played out in the future.

Gartner, a research institute for "big data", gives this definition: "Big data" is a new processing model that requires stronger decision-making, insight and process optimization capabilities to adapt to massive, high-growth and diversified information assets.

The definition given by the McKinsey Global Institute is: a data collection that is so large that it greatly exceeds the capabilities of traditional database software tools in terms of acquisition, storage, management, and analysis, and has four characteristics: massive data scale, fast data flow, diverse data types, and low value density.

The strategic significance of big data technology is not to grasp the huge amount of data information, but to professionalize the processing of this meaningful data. In other words, if big data is compared to an industry, then the key to the profitability of this industry is to improve the "processing ability" of data, and realize the "value-added" of data through "processing".

From a technical point of view, the relationship between big data and cloud computing is as inseparable as the heads and tails of the same coin. Big data cannot necessarily be processed by a single computer, and must adopt a distributed architecture. It features distributed data mining of massive amounts of data. But it must rely on the distributed processing, distributed databases and cloud storage, and virtualization technologies of cloud computing.

In the Internet circle, if you don't talk about "big data", everyone will stare at you as if they are looking at one, but in fact, talking about data itself does not make much sense, big data is more like a way of thinking, just like the view of the book "Big Data Era" - "a large amount of data can make an industry better understand customer needs, so as to provide personalized services". Based on this, only by analyzing big data can we finally achieve accurate and intelligent matching between data and requirements.

This is a derivative that conforms to the development of the great era.

Big data is a very new concept.

The red envelope activity made by Weibo in the previous life is a manifestation of big data.

First of all, the foundation of big data is quantification and quantification...... And then what?

A complete data drilling process is nothing more than this: a big data warehouse based on user data → a real data center core data asset→ data reuse based on user data behavior analysis→ so that the value of data can be sublimated.

Before that, there is an important data collection process. The primary reason why Weibo's "Let Red Envelopes Fly" campaign has attracted the author's attention is the people-friendly nature of its data collection. In itself, Weibo is a new media with a very strong interaction with the people, coupled with the red envelopes labeled as folk customs, the form of science and technology + humanities makes both sensibility and rationality, thus casting the "down-to-earth" human quality of this event.

Of course, such a "down-to-earth" human quality is ultimately due to the win-win strategic awareness of enterprise participants. If "making profits" is only one aspect of the original intention of the event initiators, then another important reason why major corporate Weibo is keen on "red envelope" activities, in addition to increasing the purpose of fan interaction, may be direct marketing benefits. After understanding such a "conspiracy", you will understand why even the 2014 CCTV Spring Festival Gala was involved in this festive activity of "red envelope flying". According to reports, at 1 o'clock on the 31st, the specific amount of red envelopes issued reached 11,470,000, and the number of fans of the Spring Festival Gala also soared, once reaching a considerable growth rate of 63.83%.

Regarding the discussion of big data, there is also a black box theory circulating in the circle, that is, in the process of deduction of big data, one side inhales big data, and after the black box processing, the other side continues to flow out conclusions. Therefore, through the "black box" treatment of this event, the former official of a certain wave came to the following conclusion: In the southeast coastal area, which pays more attention to the Spring Festival "begging for money", this "red envelope feast" is obviously more popular. According to the data of only 3 days after the event was launched, netizens in Yangcheng, Beijing, Shanghai and other provinces and cities were the most active in "grabbing red envelopes", with participants from Yangcheng leading with 13.9%, participants from Beijing and Zhejiang Province with 7.2% and 7% respectively, and participants from Jiangsu Province and Shanghai Province also exceeded 6%.

Divided by age group, the "post-90s" generation has become the favorite group to "grab red envelopes", which fully demonstrates the enthusiasm of young people on social media to participate. Among the participants of the event, 57.8% were "post-90s", and more than 60% of the participants were "post-90s" and younger "post-00s".

Compared with men, women have a greater interest in "grabbing red envelopes", accounting for 53.6% of the participants.

Interestingly, a certain wave also counted the "lucky rate" according to the constellation division at that time. Scorpio, Libra, and Virgo have the highest odds of winning, with nearly 30% of winners falling from these three zodiac signs.

In addition, big data also has its humanistic value, that is, to fill the "information gap".

Of course, the above superficial conclusions are far from being a big data gold mine. Only by continuously mining with a discerning eye can the value contained in big data be gradually released. vertex

For example, why are five provinces and cities such as Yangcheng the most active in the red envelope grabbing activity?

In fact, a brief study is clear.

According to the main data of the sixth national population census in 2010, the top five provinces in terms of permanent population are Guangdong, Ludong, Central Plains, Sichuan and Jiangsu provinces. Guangdong Province and Jiangsu Province are the top populous provinces in the country, and the population base is large, so there are naturally more Weibo users. As for Beijing and other places, count the number of software parks in these three places, and you can know why they can lead the trend of science and technology.

At the same time, according to the close connection between technology and the economy. The more the economy reaches the region, the higher the degree of digitalization, and the reverse is also true.

Therefore, the above statistics are not only a technical problem, but also an increasingly obvious social problem - the "information divide". Research data show that the difference caused by the digital divide is becoming the "fourth major difference" in China after the "three major differences" of urban-rural differences, industrial-peasant differences, and brain-body differences. In the era of rapid development of information technology, this is a particularly noteworthy problem, and the direct consequences it leads to are imbalance in social structure, imbalance in rights, inequality between the rich and poor, disorder of order, lack of development, and even social antagonism and conflict.

Taking Beitong City, where Zhou Fangyuan's hometown is located, as an example, this fourth-tier city still relies on TV and Internet cafes as the main channels for media receiving terminal configuration and information acquisition. When the mobile Internet became popular in Beijing, Shanghai and Guangzhou, here, mobile phones are still only used to listen to calls and receive text messages.

The case in the East is still the case, and you can imagine how barren the degree of digitalization in the Midwest can be. Some people figuratively say that the distribution of topographic cascades in China is similar, and the degree of use of digital technology in different parts of the country is also distributed in cascades, but in the opposite direction.

For a long time, the government has attached great importance to the "information gap" between different regions and strata, and has worked hard to bridge the "village-to-village" project and other projects. However, it is mainly the gap in access to information that is bridged. The information use divide, another branch of the "information divide", has not received enough attention, i.e., inequalities in the use of information across regions and groups. For example, compared with the upper class, the low-income group obviously prefers the entertainment function of the media, and pays less attention to the content that improves the living state through the media.

Only by working hard to bridge the gap between information access and information use can we truly fill the invisible but real "information gap", which will eventually become the positive energy that big data should eventually release.

Following this line of thought, the timeline is used to compare the differences and root causes between the post-90s, post-80s and "other post-generations". This will be of far-reaching significance to improve government management functions and enterprise decision-making capabilities, and innovate development models. If the mining of data cannot rise to the height of humanities, then all databases are just a set of cold numbers and a naked profit tool.

But big data, while good, also has something to be disgusting.

For example, Zhou Fangyuan just bought an invincible triple camera, and then the shopping website reminded him to buy some entry-level SLR, class4 memory card, dog head and tripod within 100 yuan. A little bit of equipment friends should know that he spent so much money to buy a full set of cameras, and the rest of the equipment he needed should be a red circle lens, a high-end tripod, a memory card above class10 and a jeep, and then he had no choice but to let these emails be deleted forever.

Just like RFID transformed the retail industry back then, big data is also changing e-commerce and social platforms, and e-commerce bosses think this is a smart thing, but for some users, it is really uncomfortable.

To put it simply, it can be summarized into several points.

First, Zhou Fangyuan was reluctant to help him choose other products. Although e-commerce companies are in contact with products every day, the buyers' purchases are not involved in the use of products, and buyers are only exposed to the price. So, merchants and their big data systems don't know the product better than the user. For example, 3C, users know more because they are participants, they are bought with their salary, and they will work hard to research the product. Take a mobile phone as an example, how many buyers' mobile phones are not sent by the supplier? So he can't look down on the products that the e-commerce company helped Zhou Fangyuan choose. It is useless to understand the user, and it is useless to understand the product.

Second, Zhou Fangyuan believes that merchants do not have enough control over his consumption behavior. He hasn't bought meat online, is he a vegetarian? If he buys his mother, Fulon won't he buy baby formula? Not necessarily.

Third, even if Zhou Fangyuan takes a fancy to the products pushed, he will still insist on seeing if the sales policies on other platforms are more favorable. Because the price of the network is still very messy, for a 20,000 yuan camera, the e-commerce price is 1% privately, and the manufacturer may not open its mouth to complain to the e-commerce, but for users, it is a real 200 yuan, and it is worth patiently placing an order after comparing prices on major platforms.

Therefore, for the use of big data in similar e-commerce industries, Zhou Fangyuan believes that there are two paths:

The first way: desperately grasp user data, including data docking and exchange with other financial and commercial systems, comprehensively judge user consumption habits, and then try to guess user consumption habits, and then use all the ways that users can receive to tell users product information and promotions.

The second way: low prices every day, there are main promotions, no promotions. Wal-Mart does not have a membership system, but it has the most cost-effective customized products, so as a user, will Wal-Mart feel that it is not worthy of being a Nanbo bowl in the industry?

The first road was full of people.

Just like a few years ago, when someone held a meeting to decide the fate of the company, they would persistently call the person to ask if their water heater was comfortable, and the person never bought this brand again. The initial user of over-service is fresh, and if it does not cater to users more after a little stage, users will rebound.

Sadly, there is no one on the second path, and users themselves cannot choose the second path. In fact, big data is similar to terminal on-site interception, and the holiday counter is full of business, market, promotion, promotion and even etiquette.

Of course, this is just one example of the application of big data, but it can be seen that big data has been used rotten in previous lives.

But looking back, big data is a major trend in the future. Even if it has been used badly, various Internet companies will still continue to study their own big data, because the future of big data is artificial intelligence, which is one of the few advanced forms of scientific and technological development that human beings can see at present, so this goal alone will also promote these companies to move forward. What's more, if you don't study big data, others will study it, and when others have gained from research, you who have not studied it will be defeated.

Zhou Fangyuan, as a reborn, how could he let go of such a thing as big data?

This is the big data center of Yuanfang Group, and it is also Zhou Fangyuan's main itinerary today.