This newspaper worked with the first financial brainstorming program to explore the problems of the big data age. Participants in this discussion were the author of a large data concept, Professor Victor Maire Schoenberg of Oxford University, Microsoft Asia Pacific Research and Development Group, the chief architect of cloud computing operating system Xu Mingjiang, Shanghai Information Experts, Professional Committee experts, Wangxiaoyang, director of the Computer Institute of Fudan University, Jian, a global partner at Kearney Management Consulting, Eugene, director of the Institute of Modern Philosophy at Fudan University, Donshau, a leading financial commentator, Shi Shusi.
1 What is the big data?
Victor: I think it is the new gold, I think it is the most important resource in the 21st century, this kind of resources for the society, enterprises, individuals can be successful, or will suffer a great role. Explain, although we have data before, we can put them together and analysis is very expensive, so we have more attention on the physical resources, is the real gold, nuggets, such as labor resources. But only recently do we rely on people's knowledge, innovation to create wealth, the previous step, we can be based on data, because the data collection and analysis, the degree of increase in costs have changed, and then our data can reach a certain scale. In the end, whatever you are looking for, whether you are a person, a company, an organization, or a society, nothing is the so-called new gold.
Why is gold's value going down so bad lately? Because old gold is worthless, no new gold is worth it.
Donshau: My point is a bit similar, the first is the cloud, the second is the relationship, the third is the future. As Mr Victor mentioned earlier, because of the cloud era, the cost of storing a large amount of data is very low, so that we can make use of large data to work analysis, recently because of many things in the relationship, there are more relationships are understood, so can predict the future situation. In your own words, is to listen to spend a lot of time, see a lot of friends, we look for job opportunities are also good or know the work to help partners, or in such a large information, so many people put his own information on the above, is to do one thing, is analysis. If you are 40 years old and want to be the CEO of a creative company, you are now 20 years old, how to plan for the next 20? This is a very interesting thing.
There may be different possibilities in the end and it will be the best way to find out for you. The possibility is in front of the highest rate of opportunity, how to choose or individual decision, so big data does not obliterate individual consciousness.
Shi Shusi: The big Data first changes the way we look at the world, which has a dramatic impact on many of the values of this era. For example, because in the past we oriental people particularly like a word called cause and effect, we think that good and bad, in fact, according to the data of the Henghuo survey, in the streets of the people who actually have nothing to do with the moral, Qin life is Yue Fei's twice-fold, a lot of corrupt officials in the discovery before, it is indeed an infinite envy of life. Therefore, through large data we can use a new concept to look at the world, the world is related to the construction of a new relationship, only the development of technology to a certain level, to achieve such heights.
At the same time, in the big data age, the bottom line we should adhere to is to adhere to, but it does tell us the truth, because science is telling us the truth. I have a wish that the big data I just talked about is new gold, and I hope it will be used more for social welfare, for example, to save the Seismological Bureau. This avoids many humanitarian disasters and loss of property, and concludes that we used to think that God was a philosopher or a philosopher, and now finds him an old urchin.
Does the 2 data have any impact on work and life in all areas?
Wangxiaoyang: Big Data affects wisdom. How to understand? The concept of large data itself is data acquisition and processing, to a certain extent our society, managers, can benefit-from the city, a manager can gather these data and processing methods, so that we can use wisdom to manage the city, from traffic management, public health, and other aspects of management, This management is the need for data, the data generated wisdom, and then reversed to manage our model.
For example, in public health, the collection of data to date has actually been carried out for many years, its data collection is not for large data to do, in fact, for a convenient-convenient for everyone to see a doctor. And your electronic case, let your doctor more humane, or to the doctor can be faster, more convenient to get acquainted with the disease, but in this case, once the data collected so that we will be able to better understand the health of the whole city, so, the medical data mentioned just now is actually the original intention, Large data we can actually see the unseen problems. For example, some of the more general trends of the problem, where the epidemic is more, or how it circulated, and so on. These things we can not see, this situation is the big data to help us.
Xu Mingjiang: First, for example, there is a ball and an ant, and the ball says to the ant, to do things in the three-dimensional world is too good, you see how many ants on this line I saw at a glance, the ant said I really do not believe, I have to follow this line crawl, climb the end of the counter did not fail I know how many ants. This can see three-dimensional and two-dimensional difference in one dimension, the difference is so big, so big data first it is not large data, not the same data more to become large data, but in the original two-dimensional, the original database on the basis of the establishment of a one-dimensional, to give it a new look. For example, if you are in the United States, you are in debt, except that the creditor is interested in you, and others will be interested in you-if you are in debt, suddenly you can repay the debt, then the bank will be interested in you. 11 years ago, the American capital number invented a large data application, it can find out who owes the bank money, owes the credit card, and then it observes your consumption data, and when it finds you can start to return it, he buys you back at once, and then he eats your interest. Capital number the company in 2001, the growth rate per quarter is 20%, because it is a large data program, it can hit the high percentage of this, it is from where to find the data? From Wal-Mart and from a variety of consumer data. From this example we can see that the big data this original data analysis business intelligence added a layer, business intelligence can not tell us what others will and can do.
About our company's prediction of the Oscars, except for Ang Lee's prediction is not right, the other is right. In fact, our prediction is to all the people have done a probability, so did 19 predictions of the right, we put in the first probability of the winners, the following 4 is the second probability, so the director of Ang Lee we put in the second probability, we put him in the back.
This prediction is very related to large data, the first big data need to have IQ, IQ, that is, this model is very good. The IQ of our company is called Gadavi Roschald, a person in our research department. and others, I would like to tell you, what is the difference in IQ of his person? His IQ is a very simple aggregation of the model, in addition to IQ what else? After the IQ also have to have diligence business, diligent diligence. Diligence means that he is very diligent to find data, to find a variety of data, but also to find very practical data, so he was on the Internet, social networks are looking for. Have some data that can't find, how to do? He is looking for someone to do research, and then find someone to do, so he has IQ, and the diligence business, enough? Not enough, five years ago this kind of thing cannot be done, why? Five years ago he wanted to do such a large amount of data, his small budget as a graduate student can not do, but the advent of cloud computing, he could do it. Can extend this data, with a lot of processors to deal with, now he is using the cloud to do such a calculation, and finally succeeded.
Jian: I'm writing about opportunity and danger, which is crisis. I agree with Victor's conclusion that this is a new gold mine, or a new opportunity, but don't forget that it poses a lot of dangers. If we can't handle big data well, in particular, many Chinese companies that are exposed to our daily work, most of them even lag behind in the most basic data analysis, which means how quickly we can transition to the big data age, to face big data challenges, and if not prepared, then I'm worried , it will be like many new technologies in the past, it is easy to cause a lot of enterprise Handan-even walk has not learned to learn to jump, all of a sudden to the big data era, enterprises do not know how to really let large data play a role.
In our industry, a lot of product innovation is done because of the big data. When it comes to the disruptive innovations in the big data age, it actually talks about the same problem, because at the same time, the innovation, in fact, to deduce and subvert many of the original things, including our consulting industry, many services and products to be updated, but also to keep up with the times. For example, we have a big global retail business, it handles a huge amount of data every day, then in the vast data, although there is a technical means, it still needs to find a good entry point, to solve the big data how to apply to the business, change the business model, to bring value to business innovation. Because this large data to better use, and then cheap or investment, or to change, hardware, software to do all aspects of configuration, and even the corresponding organization to make adjustments, an enterprise to make further adjustments to adapt to the needs of large data times, in order to make large data play a role. So our job is to help companies find the value of their creation, to establish business models, to prove that in this regard to make such an investment, so that large data to play a role is worthwhile.
Eugene: I would like to make a different view, because the human mind has a characteristic, he exaggerates the things of enlightenment to the world. Like you see three swans are white, but in fact, there are 1000 swans are white, can be found in Australia A black swan, all swans are white to overthrow the principle, I think the big data this problem is important, but how to treat it correctly, can not go to extremes. Large data reflects a way of thinking about how people understand life from a quantitative relationship, which has been taken seriously since ancient times, although the concept of large data was not used in ancient times.
The number itself is becoming more and more important to life. Philosophically, it has practicality, such as pi in Mathematics, pi, which equals 3.1415926 ... It includes all the big data, and it's easier to understand One-third, One-third is another way of writing is 0.333333 Infinite is extended, so the hacker in the logic of the emphasis, this infinite tolerance in one-third this finite, limited contains an infinite expansion, including all the data, which embodies the spirit of practice. Looking at this data from the perspective of this practice, I think big data has an important place in contemporary changes, but look at it with a vision, not exaggerate or shrink.
3 How to understand One-third to the life of all the data summed up?
Victor: I don't agree with Miss Yu. Numbers have a long history, but we used to deal with these numbers very limited, light technology is not enough, can analyze the data, such as numbers, it is just a number for you, this meaning is not important, you can also use a Chinese character or a letter to express, that from this point of view, Big data is just a long, long number, you can remember with your heart.
But in fact, the value of large data is that the whole process of data collection, the need to use analysis to understand. For example, how to do preventative maintenance, how to prevent outbreaks, etc., we do not put this number simply down or back down, but through analysis, through the analysis of data statistics, through the collation of the understanding after the analysis, this is not your back down a number on it, this is very big difference.
What kind of subversion does the 4 data age bring to life?
Victor: First of all, commercially speaking, I think there are three elements to remember: one is that decisions in the business world will change, and it will become increasingly clear that data is to be spoken.
In the United States, the largest internet company, probably Google, has 3 billion search requests a day. One day they were ready to use blue on the screen, and then they chose a special blue, but he was going to test 41 different blue to see which one was the most popular. He wanted to decide for himself: I am the chief designer, I chose a kind of blue. But his boss said: No, I need empirical evidence to tell us which Blue is the most popular. But the Google chief designer resigned, saying I am the chief designer, and I am the clearest. A lot of tests have found that there is a blue that is open to the naked eye and the designer's choice of blue, but the other is produced by testing the blue, more popular, with more clicks. It is more effective to make decisions through empirical evidence. There are a lot of similar examples, saying I've been doing this for decades, and I'm certainly right about that. This traditional social concept and way of thinking will be challenged, our decision must rely on data to speak, this is the 1th.
Second, when we go out to speak, we should be careful not to misread the data, the wrong data is not. That is, if the original material is wrong, the raw material is rubbish, out of the thing is certainly rubbish, the company out of these data are relatively easy to understand, but may not you should be familiar with the data.
The third is the challenge. It is the general industry, especially the computer industry, that the data will go beyond them, and this may be a challenging proposition. If you don't have enough data, you're not going to catch up with a fairly mediocre model of a lot of data, which is why data goes beyond those industries. such as machine translation, in the 670 's, IBM spent a lot of money to use machine translation, it's going to get some language rules into the machine, but it doesn't work so well, it has a new idea, it's not to put the grammar rules of a language into the machine, but to translate the English-French bilingual into the Canadian Parliament. By inputting thousands of translations into it, it has a large number of cumulative databases on the organization, a much better effect. And Google in this field has more data, all of a sudden the translation is more mature, better results. It can be said that this data makes it go beyond the software. Because of the power of today's big data, it's easy to get the information you want, but about a decade ago, it took 500,000 servers, lots of storage and data processing patterns before you could start a new business. If you want to enter the business today, you can use cloud computing to test it. For example, there is a company called Tissede, it has a lot of products and prices, it acquired some data to predict whether a product is shelves or a shelf, although they have a large number of customers, but the company employs only 13 people, so it has a lot of servers, they have a large number of data. It can be seen that the stage not only allows large companies to do, but also innovative small companies can compete on an equal footing.
Wangxiaoyang: In fact, the change of our whole way of thinking, the so-called is the experimental thinking, more important than theoretical thinking, which I do not understand. In fact, the example given by Mr Victor just now is that in many cases, we use the data to verify what we want to be able to do before, and some of the wisdom is actually unearthed in the figures, which is probably a language from different places. Based on the case of large data, there is actually a so-called cyclic concept, is equivalent to saying that you have the wisdom to verify, the verification data has generated a variety of wisdom to do this understanding, so from this point of view, I think it is the case of large data, there is no subversion, but to say an improvement in our understanding of the world's improvement. As far as public health is concerned, one of the most common examples is Google, where there is a so-called trend forecast, which uses the words that netizens search for to predict.
What is the so-called prediction of influenza? Very simple, it is to analyze the previous data, said that in the region where the flu occurred, the region that time people are using what words to search, so you can do statistics. After doing the statistics, what do you mean by going back and using these search terms to predict the flu? It's not necessarily that this kind of data or big data will give us a sudden new understanding of the flu, in fact, it is Google's engineers who have an idea that we are like influenza pandemic, which is related to everyone, and everyone will use search to get some information about influenza, there is such a link. How do you find this connection? This is to use data to find, with the so-called large data, to achieve what we already have some of the concepts of things, after it has been achieved, can make predictions. So from this point of view, and not necessarily have large data, we can put all the wisdom is lost, we do not have IQ, as long as the data is good, this is certainly not the case. It must be the IQ plus the data, and then it has a positive and negative concept, which is what big data should do.
Donshau: I have different ideas, I think what Mr. Victor said just now is very interesting, that is, the demand for wisdom, the big data age is not the same. In the big data age, the need for wisdom can be lower, can produce better results, this is an interesting thing. He has just mentioned an example, before it is difficult to do translation, your rules must be particularly strong, concise and complete, in order to have 60%, 70% of the accuracy rate. But in the big data age, we do not have to think of those, do not spend wisdom to speak so complicated rules and routines, simply put hundreds of millions of translated articles to the computer, in a statistical way to find which case, the translation of the word another meaning is relatively right. The demand for wisdom is actually reduced, but the effect may be better.
Jian: Maybe our understanding of wisdom is ambiguous. I think Mr. Victor said I understand, because he has another book called "Delete", which is devoted to this triple wisdom, talk about trade-offs. Because with the development of storage technology, the Internet, he said more knowledge, knowledge requirements can be low, but for wisdom, I think that understanding is different. The wisdom I understand is that you judge the fundamental, real insight of a thing. Is that your insight into a thing needs to be, not weakened or unwanted by the presence of large data, but precisely because the presence of large data requires insight.
is the 5 data age really coming?
Wangxiaoyang: The big Data age is not coming depends on how you measure and measure. Now the amount and type of data, as well as the method of collection, means, the means of processing, has definitely reached the "unprecedented, after no one" feeling. In this case, we've come to the big data age from this ability to data acquisition and data processing, but we're just starting out with data using data.
But the big data changes our life time, has not come completely, but for this we have done a lot of preparation, this is the city management question. We have done a lot of preparation for the big data age, such as a lot of preparation for data acquisition, how to use this data to be our intelligent city, this is one of the biggest problems.
Xu Mingjiang: From a commercial point of view, I use it as a personal thought that it is coming. For example, poet, a pharmaceutical company, he can according to the nature of the weather, for example, if the winter is particularly cold, many allergic animals will hibernate, April or May when the sudden heat, pollen also began to many, this year, a lot of people will be allergic, and so on, it is through the market marketing, such as Claritin can release the medicinal materials.
Victor Maire Schoenberg: U.S. President Barack Obama has said that despite the government's attempts, he has always lagged behind businesses and other groups in society. So this kind of activity can fully inspire the data, provide to the public, and the company can take the data, so that companies can use the data more innovation. This is an idea, maybe there are some ways, such as business methods, I think can play by the wisdom of the enterprise, such as Microsoft, the wisdom of some smart companies, but also helpful, including cooperation with the Government to manage the community.
Shi Shusi: I have a feeling that when business titans talk Big data to Dick, we all have a chilling feeling, because even though we are all fair in the big Data age, we can say that small companies can get fair competition, but in fact, the big numbers are the Giants, They have a unique advantage in robbing us of the money in our wallets, because the definition of a company is that it is mercenary in the realm of law. But we are eager for government departments to use large data to provide us with the benefits of the services, but like some smart cities can not really manage the wisdom of the case, so I am very worried about the future of big data to China. And even if good companies use big data, it also has to face a reality, such as we advertise on TV, why people are still a lot, because China's rich and poor gap is particularly large, if you have mastered all consumer data, and most of them today is invalid data, so you still have a choice of large data process , called the purchasing power of large data, so a variety of problems will appear in front of us, is that society is what we need, but it has a lot behind the scenes to see what is not clear. We are worried about being used by commercial giants to do more to exploit consumers.
Jian: I think it's the same problem from an enterprise standpoint. What I was trying to say was, first of all, many Chinese enterprises today are not really ready to welcome this large data, because we are still in the relatively elementary age of basic data analysis, many of our basic data today are not used, do not say big data, is small data today is not very good use. There are a lot of fake data because the input management of these data is very immature, my own work in contact with a lot of enterprises, business today to do a few things we are doing, there are ERP system, there is a database, there are data to be stored, but I found that many Chinese enterprises to cash the data management does not have the sense of standardization, Not well utilized. There is this fear: when the last big data age comes, we originally Chinese enterprises in this data analysis utilization is not good at, today with large data gap will become bigger, after the international giants have a mature data analysis method, many sound business model, it will make this gap becomes larger and bigger.
6 in the big Data age, what will the next prophecy be, and what will the next judgment be?
Victor: Then how can we make life more efficient than it is now, that it is possible to make the city smarter, and why? I emphasize that we are likely to improve our public health, improve education, we have the ability to collect data, the public transport of Tonghua can really meet the needs of the people, not just politicians, and energy consumption will be better detection, prediction and management, so that our city will be more intelligent, so that the city's life better. 150 years ago, it was predicted that life would be shorter if it lived in a city, and life in the countryside would be long. And 150 years later today, the longer life, with large data we will be better, but there is a condition, is that the decision makers, they must use these numbers to be able.
The next step is how the experts do it. In fact, this involves in the data age, data points are limited, then we collect data, as long as we collect enough data to solve the problem. Because very complex, very few data points, so our data points must be collected to be high-quality, now is not the case, now is more and more chaos. Explain what's called more and more messy, more is the data points, about a phenomenon we want to study, we can do more data statistics, such as in the United States, you have a DNA gene map, so as long as 2000 dollars to know your entire genetic map of 3 billion of this thing is how to make up, So you can know those 3 billion fine pairs, now if there is a genetic makeup may cause what kind of cancer, you can look up the genetic map, said I am not susceptible to this disease, this is why can predict whether the cause of cancer. Then there will be some inaccuracy in more data, so, I said more and more chaos, so here allow a little bit inaccurate, or can be a bit messy, this so-called chaos is to mean, not to say that every data point to achieve the highest accuracy, the result is, not 100% perfect, But in such a direction as large data, or we need to know a direction at the right point of data. Knowing the direction is more effective than knowing the perfect data later. Traffic forecasts, for example, may seem too late for the current traffic forecast to be 20 minutes later than the actual application, but if this is a one-week message, that's enough.
Wangxiaoyang: The big Data age is more understanding of our city, and the so-called understanding is that you know what's going on in this city, which is very important. In the past, the city's management is a pat on the head, sometimes the head to take a good shot to shoot the head can make a great city, but sometimes? The head may be too outrageous, and in this case how we use it in the big data age is what we say. And for the performance can also be considered with large data, said that the number in the end is not good for its achievements? Is that the name is a big part, and the big data is not just about understanding what's going on in our city, but also about what people in our city are thinking? This is very important to the city management, the city is not only a hardware facilities, not only the subway and high-rise, people in it is very important.
(Responsible editor: Lu Guang)
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