Are these Years a lie? Big data isn't that amazing.

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Hear "Big Data", do you feel the same as most people, and have a vague outline? Nicolas Felton, Nicholas Felton, a US data visualization expert, says that big data is a massive, complex data that goes beyond the processing power of traditional data management tools, metrics including data volumes , processing speed, and type of data.

And is the big data really as useful as the legendary one? At this summer's Davos forum, what is called "big data or big bluff?" Debate will be on the stage as scheduled, and participants are enthusiastically discussing whether the opportunities presented by big data have been oversold.

How useful is the big data?

"Very useful!" The current Minister of Information and communication technology policy in Japan, the mountain Ben one too at the beginning of the debate on the very big data. "This time Tokyo can successfully bid for the 2020 Olympic Games, public support is very important." At the beginning of the bid, the Japanese people who supported the bid were only 50% to 60%, and in order to raise popular support, Tokyo set up a PR team to promote the bid. The significance of hosting the 2020 Tokyo Olympics through social networks such as Twitter and Facebook has been very good, with popular support reaching 83% per cent before the Olympic bid. "Referring to the success of the bid, mountain Ben is very excited," This is the use of large numbers of credit. In addition, big figures have helped in political campaigning and coping with natural disasters. 2011 Japan 3 11 earthquake affected many cities, it is through the statistics of large data, we have properly placed all the victims, and carried out follow-up rescue and reconstruction work. Mountain Ben One too adds.

Outside the debate field, vendors of large data solutions paint a big and exciting picture: How do retailers know about the consumption habits of different types of consumers in the retail sector? First of all, we should establish an information system to analyze the customer's gender, age, income level, transaction level and other basic information. And through the long-term trading system to capture consumer habits, and then from different dimensions of their price sensitivity, consumption time, and then can provide the corresponding products to meet the different levels of consumer demand. In addition to being able to choose the right promotional time, location and promotional items, a sophisticated consumer database can also be hit precisely-precision marketing. Electric dealers have a lot of space in this field, for example, according to the consumer's browsing record on the Web page, to different consumers to push different ads: also open their own blog, men saw the car ads, and women see the perfume ads, are their respective brands of interest. This kind of marketing to the enterprise undoubtedly has the very high attraction.

In addition to online and offline retailing, the financial industry has a strong demand for a large number of data-processing analysis, while the traditional industry's supply chain management and financial system upgrades require data collection and processing capabilities. In the social public domain, a large amount of data must be collected and processed from the planning and design of infrastructure, the diversion of traffic to the emergency management of disasters.

Three questions.

No one doubts the usefulness of the data, but the sound of big data is mostly concentrated at three points.

First of all, do we really need so much data? Jermy Howard, president and chief scientist of the US Kaggle company, argues that the relationships that humans need are not complex, and that too much data breaks people's attention. "It takes a lot of time to collect such a huge amount of data. The best way is to extract only the most important data and not waste time on the collection and processing of irrelevant data. Bright Si-mons, president of Ghana's Mpedigree network, also believes that big data is at risk of centralization, and that for people, it is more important to "insight", the autonomy of individuals, to pick out useful parts from the big, complex data.

Second question: What about privacy? When shopping in the supermarket, your membership card will record your consumption information, the relevant merchandise discount promotional activities will be sent to your mobile phone. When you surf the Internet, your cookie information is read, and if you browsed a couch a year ago on a Web site, it would automatically pop up ads and promotional messages on the couch, whether you wanted it or not. You in Weibo, everyone and other social networking sites on the "write a good paper hard" state, the result of every day there are countless papers on behalf of the agency to come to the door. Our personal information is collected by a variety of data suppliers and becomes a free material in the data industry chain. More worrying is that any information that has a privacy barrier on the web is technically accessible. In the big data age, we have no privacy, no secrets.

And that raises the 3rd question: How to secure data? As long as the data form exists, it is inherently a security risk. The database may be stolen, hacked, distorted, and replaced. Online ordered a chicken rice to send a fish pill rough noodles are small, wedding anniversary to send the wife's flowers are written on the name of others may trigger a murder. Information about national security is very sensitive. Once data security is compromised, large data can be a big risk.

Technology is innocent.

Looking back, the concept of large data from the rise to the hot but only a few years time. In the 2009, the term "big data" gradually began to spread through the Internet. The Obama administration's high-profile announcement in 2012 of its "Big Data research and development program" marks the traditional offline economy in which big numbers are really starting to enter the mainstream. From 2009 to 2012, it was the time of the global flowering of e-commerce, and it was the collision between the Internet and the traditional economy that really spawned the "big Data" of today's almost universal concern.

Large data not only equals "data mass", but also includes cross-domain data fusion and data flow, which includes not only structured data in a neat form, but also unstructured data in many forms, such as sound, picture, text, and numbers. To collect and process such complex information and to create value through analysis, no one doubts that such technology will profoundly affect people's daily life.

But how to use this technology has nothing to do with technology itself. A large data engineer, without a regret, said: "It is expected that large data technology can bring some changes to society, such as urban planning, transportation planning and other applications can greatly facilitate people's lives, but the current large data technology business applications mixed." The use of consumer data is a bit of a consumer-controlled business, and the big data platform that we do for many banks is mainly about face engineering or the need to deal with regulation, and the impact of big data doesn't really work out. ”

Sumeng, an associate professor at the Guanghua School of Management at Peking University, says the big data is now used only in service industries, but in fact large data can be applied to all levels of society, such as healthcare, energy and security. The current problem, one is that large data does not flow up in the enterprise to form Island-type, independent data, did not play a greater role in large data. The second is the lack of a complete ecosystem, not formed from the collection, excavation, analysis to the application of the industrial chain, and finally the lack of professional talent, "the big data age has not really come." ”