So for small and medium-sized enterprises, in fact, they are also in also very concerned about a big pattern of change, to them to be able to bring the expansion of market scale, and even to achieve the industry leading such an opportunity, so this newspaper and the first financial brainstorming program cooperation, focusing on small and medium-sized innovative enterprises how to grasp the opportunities brought about by the era of big data, in the face of what kind of bottlenecks and challenges. Guests participating in the discussion were: Zhang Shaofeng, CEO and vice president of Beijing Percent Information Technology Co., Ltd, Liu Li, CEO of Ordering Secretary Lemony Vegetables, Zhang Yiming, CEO of Beijing ByteDance Technology Co., Ltd, Ding Zuyu, executive president of E-House (China) Holding Co. Li Yi, co-founder and executive director of Venture Commune, and Kong Fanren, chairman of Qizheng Mugu (China) Consulting Organization. 1 Big data is turning from a technological buzzword into a social wave, impacting social life, but what exactly can big data change? "Big data is not necessarily only used to connect people and information, it may be used in health care, finance, typically for individual users to better access to information, the first feature is that you use at any time at any time there is new content, the other more importantly, can be used to each person's interests, analyze each person's behavior, for all users to recommend it interested in the content. The process of user reading is I for myself, but the result is actually I for all. " Zhang Yiming: big data for me is to change my ability to connect users and information, I can use big data to change the way users get information. As far as the company is concerned, our company is able to use big data to be able to connect the user's information, we are able to analyze massive amounts of information, process massive amounts of information, and at the same time, analyze massive amounts of user behavior, and connect the information and the user together. There was no such opportunity before, but only after more and more user behavior data can be analyzed, there is this ability. At the same time it will be possible to give users better discovery. Big data is not necessarily only used to connect people and information, it may be used in the medical, financial, in our case more typical is for an individual user to better access to information, the first feature is that you use at any time at any time there is new content, indicating that we are access to a massive amount of data, this is called big data, but the other is more important is that we use the interests of each individual, analyze the behavior of each individual, for all users to Recommend the content it is interested in, on the user's side to do the mining of a large number of users' data behavior, the user reading process is I for myself, but the result is actually I for all people, that is, better access to information to provide help. Shaofeng Zhang: Big data has changed my life and work, I can use big data to change the operational efficiency of enterprises and people's lives. What is big data, is a different industry, a different field of data fusion together when the data can produce qualitative change. Because more data, an industry has more latitude. Each additional latitude, the value of the data is exponentially changing. The impact of big data in my look, I can provide services for other enterprises based on my data on top of this big data, let's say precision marketing, I give an example, is the example of Yintai Department Store, Yintai Department Store to do the so-called OTO, online and online fusion to break through it because of competition with e-commerce, it wants to do something, the user is to go to the shopping malls for free on the wireless, paving the way to the free wireless point, an Internet he was Hanging percentage point number, percentage point do you know what this user preference, know, you push a coupon to him that the second floor has an erotic lingerie on sale, the top brand, do you want it, may be in the fifth floor have your favorite flavor, you like the Congo dish, a very rare dish, also played, is because we go to analyze the whole online user preferences. Chai Ke: Big data brings new data services and products. I think although we are an entrepreneurial enterprise, the volume is still very small, but we have more than one million girls every day to actively participate in informing the relevant physiological data, or all the Asian population, so that I am able to through the data, in the disorder to find a pattern, which is more valuable for the development of products for the Asian population and the development of drugs, our company now has close to two thousand finished and in Asia. Our company now has close to 2,000 women in Asia, and I believe that our data is still persuasive, and I may conclude by saying that I also believe that the era of big data is not yet an era, but data services and data products are an era that our entrepreneurs have begun to explore and have already had a prototype. 2 For entrepreneurs, is big data an entrepreneurial change or a lull? "Big data itself is not a lull. But any revolution, when it first comes, people's expectations will exceed the speed at which it actually happens, you want it to become fast, in fact, it becomes very slow, but when it really changes, it destroys the world faster than imagined. Now in fact, big data has not yet arrived, in fact, the big companies are still fooling people. " Zhang Shaofeng: I think, at this stage, many companies are fooling people, but big data itself is not fooling people. For example, IBM, oracle those companies are flimsy, they go to our customers to tell N big data concept is to sell it equipment. For example, I recently a customer, by an internationally recognized brand company said a lot of cloud computing things, my customers were fooled, bought a lot of its equipment, the results bought after the COO asked me what these can do, this is not fooled? In fact, you should think clearly, you do what application, and then in turn to buy those devices and software. Because the application is for the value, you first think clearly what value I want to create, in turn, I want to create value what equipment and software support, so I think IBM, oracle, Microsoft is all fooled, SAP is all fooled, they are not big data companies. I give another example, the former boss of oracle said what cloud is hype, cloud this thing is nothing more than the previous CS model, BS model, and then by Google to get out of the way, so oracle also engaged in a, because it does not carry out the high-end packaging, it does not sell the equipment. I think any revolution, just started to come, in fact, people's expectations are more than the actual speed of its occurrence, you want to change very quickly, in fact, change is very slow, but the real change when it destroys the speed of more than your expectations, like e-commerce a reason, so I think that now in fact, big data has not yet arrived, in fact, the big companies are still fooling people, in fact, they are not a big data companies, they are Product company, he wants to make a product, the user likes it OK. We also do not care if we are big data, solve our business problems on the OK, big data is really fooled out. I think is how I solve my problems, and then one day said OK, I packaged as big data, but I still believe that the Matrix described this matrix if it will become a reality, the future must be the era of big data, this is what I firmly believe, the irreversible law. Zhang Yiming: I very much agree with the views of Shaofeng, is to solve the problem will naturally bring some program improvements, rather than take the existing machine, the existing software, that is, encountered when we do to solve the demand for problem solving, naturally think of a lower cost, used to do big data, we are the most typical of the weather forecast, are using a supercomputer, 500 CPU, and now early have not been used, IBM has also been promoting a long time supercomputer, IBM is also a big data. Promote the supercomputer for a long time, now who buy this CPU computer, who is being fooled. Tang Jun: I think this also can't be said, they are called equipment suppliers, why do you say the arrival of the big data era, the past also has data, why is now called big data, the past is not called big data, because now the computing power enhanced, so a large amount of data through the computation from the disorder among the find order, must be by the increase of the computing power, so some of the suppliers, in fact, to the big data or bring the change, this can't be denied. This is not to be denied. We are now in the application without them really can not do, for example, when we do gold futures, you say you put the past ten years of data to find a correlation to find a trend, this is the need to calculate the speed is very fast, and then to help you quickly respond to make a judgment. Li Yi: This is actually the underlying support for big data, now the world, big data standards and discourse is in the hands of IBM, SAP, EMC, because it's very simple, you say that the bank now why domestic banks, such as the People's Bank of China, why they have to purchase SAP's software, IBM's mainframe, it is really this way, I'm now a second anytime you want to call a year's worth of data, how can data do not die, how can we do the same thing? How can the data do not die, how to deal with unstructured data, frankly speaking, this is really a masterpiece, this is not to be denied. Including now Microsoft and Google in the push of artificial intelligence, I say a word, Arabic real-time, simply let you do not have any interval to you to translate out, frankly this is not the average person can do. I'll say one more thing ah, lulled not lulled, bubble not bubble, now there is a sentence investment industry is very popular, what do you mean by bubble? You are in it, that is a bull market, you are not in it is a bubble. Now are in the inside, how is the bubble? You have to say it's good in this, this is very obvious, then the second is to say that from now on big data this three latitude, it is actually data must be collected, after the collection to be stored, this is not small and medium-sized enterprises can play, this is a large enterprise, the Chinese Academy of Sciences related enterprises in the doing of this thing, and the third is the analysis, if I can predict half a year later, it will be very cold suddenly, and even say I can predict ten years after the ice, it is very cold. Even said I can predict ten years after the ice age, the earth into the ice age, then you think about this clothing factory hurry to storage, a large number of down jacket hoarding, this is how much value ah. But to be frank, where do your data come from, and then you have the ability to analyze. Then in a sense small and medium-sized enterprises to find their respective positions in the industry chain. Liu Li: I think that although this big data is very exciting, but also does bring a lot of change, but I think it does have a bubble, why will everyone excited? I think big data gives people an illusion, from predicting human behavior, expanding to predict the future. I think that although the role of big data is great, but there is no need to exaggerate, we need to always start from the demand, rather than to say that I do this big data, the purpose is to become a big data company and go to do a big data, our big data it will naturally be along with the development of our main business, the grass hit the rabbit, naturally, will become big data. This is my point of view. 3 Playing with big data, small companies are more comfortable, or big companies have more opportunities? "Small and medium-sized enterprises, can only take data from large enterprises and so on, and then go to help them to interpret and analyze. Many small and medium-sized enterprises will do a kind of exploration, if there is a mechanism to enjoy them **** out, data as usual will exist in small companies, and may be more useful than the data of large companies. Visible, small companies to collect data, must think of the application. " Li Yi: big data is from the big guys, you see now this Shanghai elevated, Shanghai a variety of elevated, why is there a sign on it? Show red, green, yellow, how does it come? Because the elevated road below the buried sensing coils, buried weapons, so it can be collected, this is not to say that small and medium-sized enterprises can play, this is a large enterprise, the Chinese Academy of Sciences of the relevant enterprises in doing this thing. And small and medium-sized enterprises, can only take data from the big guys, and then go to help them interpret, analyze. I think a lot of people should use the cell phone APP "very accurate", which is a small company in Hefei, why flight delays and so on, it can provide data, that is to abandon and do not give up to find the Civil Aviation Administration to talk about, the Civil Aviation Administration said that this data is idle anyway. Then talk about a share or talk about a business cooperation, the company a few people in Hefei on fire, because he has the CAAC engine room data is not very accurate. The conclusion is that in the era of big data entrepreneurs start a business is to pick up the big guys do not play, is so simple, belong to pick up the leakage. Zhang Yiming: Yes, I think innovative companies can get data from large companies or from government agencies this is of course good, and then as a society is certainly the standard exchange of big data or developed, the government has this data open program better, but I think for startups to stand up their own, it is best that the application itself is the collection, I recommend information to you, you tell me your information, so that the positive cycle, perhaps not enough to start. This can be positive cycle, maybe the beginning is not big enough, like medium data, medium-large data, but the user is used, the more you use it, the better you use it, your data is getting bigger and bigger, so I think the positive cycle of the application and the collection is very important, and for the startups, this is also the opportunity. Liu Li: four small may not be big enough data, but what about forty, what about four hundred, what about four thousand, as long as there is a mechanism to get these data out **** enjoy, I believe that many SMEs may do a kind of exploration, there is a mechanism to get them **** enjoy out, the data will be in the small company as usual, and may be more useful than the data of the big companies. Zhang Shaofeng: Let's say that small companies want to collect data, we must think of the application, the application itself, whether it is 2B or 2C itself is valuable, rely on the service or the application to obtain data, rather than the upper level you give me data, right? I have united 800, maybe one is not so big, add up must be bigger than big. Chai Ke: the product services of small companies can more effectively obtain data, just like a country today the health department issued a message saying that all girls must tell me every day whether you come to menstruation or not, no girl will tell him, because it is necessary to rely on excellent services to close to the life of the girl in order to gain trust, only then will there be data application. 4 A large number of entrepreneurs standing at this point in time, how to pan for gold "big data"? "In the era of big data, to go in this field of entrepreneurship entrepreneurs, first of all to start from the user's needs, from the user's needs, to find out the pain points, with the hand of big data to solve these problems, rather than to fool themselves into. " Li Yi: in terms of big data such services, we call the revolution, it is for the original IBM, ICP, EMC, it is only a small revolution of large enterprises, for it is the cradle of the grass to beat the rabbit, by the hand to do. But for small and medium-sized enterprises, it is a big revolution, a big revolution for small enterprises, therefore, it is possible to really make a professional big data. The safest way for innovative small and medium-sized enterprises is to quickly evening big money, quickly sold, after accumulating strength, can then do something, which is more reliable. The second is that if we talk a little longer, we have spoken very clearly from data collection, storage to analysis, in fact, the most opportunity is analysis. For small and medium-sized enterprises, analytics have the opportunity, you must focus, such as doing catering on this thing well, do not want to do anything else, has been with the Yintai has this iconic department store cooperation, you have to go to do department stores, you do not want to do so many things. You just keep focusing on it, you can only focus on it, there is no other way. Tang Jun: I agree with the collection of basically no chance of the point of view, because the collection of the amount of limited after all, right? So you can only rely on historical data, but analyzing this is definitely a big opportunity. Because you want this than what? Than the wisdom. I think if you purely talk about the concept of big data, there are still a lot of opportunities, the use of these data have been collected by previous generations to analyze, based on this analysis to find your application, this is what I think to all the entrepreneurship or the future of big data in the field of entrepreneurship to provide a piece of advice, that is, there is absolutely no chance to find the opportunity to start their own business. Kuang Zhiping: Big data is to find a law in the disorder which is big data, that is, you can not predict something, but through your analysis of big data, you find something that can be predicted, this is my understanding of big data. But I just choose to analyze a little bit of disagreement, I agree that the simplest is to do analysis, but the problem in China is very difficult to do analysis of this job, because China has the most large amount of data on hand, not as much as the United States have a large amount of data enterprises so open. Some big enterprises, they have a lot of data on hand, but they are generally not big in China to open up to third parties, so you have to really want to put pen to paper on the analysis side of the words, you must first of all in the collection side of the somewhat unique contribution, of course, you do a lot of places do not allow you to collect, that you have no choice but not to do that line, for example, someone is willing to give you his cycle, which is a willingness to open up, there may be someone willing to give you the participation, so these are the things that you can capture, you don't have to capture in China it's hard to do this. Therefore, my advice is in the era of big data to go in this field of entrepreneurship, the first one from the user's needs to start, the user's needs to start, to find out the pain points, with the hand of big data to solve these problems, and do not fool yourself into it, do not start from the big data, because now there is big data, I have to do a big data, and then go to find out the end-users can use me to do this thing what First of all, you have to understand the industry you want to enter, find the user's needs, find the user in the past a lot of hope to solve but can not be solved now finally have the means of big data, I give it to solve, so this way it will not follow the trend, will not be everyone go to do the ads to push, accurate ads to push, not 100 percent of the users want to you to accurate ads to push, so I think you have to understand your industry, find out what kind of needs they had in the past, find out what kind of needs they had in the past. Find out what kind of needs they had in the past, and there is no way to be satisfied, with new and innovative technological means to solve this demand. Ding Zuyu: I now think that big data is the idea, can push you to do some innovation, but if you want to make money, to sell, but also rely on fooling. That is to say you have to persuade me with the flimsy, you will spend money to buy, in fact, the last are overly big data concepts packaged in their applications above, and then can get more than the original simple data analysis, such as the sale of 10 dollars, plus the concept of big data, coupled with the flimsy me, flimsy me dizzy, I gave him 20 dollars or 100 dollars. I think a suggestion to small and medium-sized enterprises is to think about the final payer, for you to pay the bill, of course, this I am suggesting that more think about real estate, because real estate to buy a single person more. If you can provide a good solution for real estate, you can live, live a lifetime, comfortable. Then look at other industries, automotive and so on, one by one under the row, and then which one and you can dock, you and he docked. Kong Fanren: He is a concept, a way of thinking, may be for some enterprises like Tang Jun such enterprises, like a small pit, a foot over, may be for some enterprises it really is a trap, so we now want to the value of the data, but really do not care too much about it is not big data. Whether big data is an opportunity or a flicker, I think we can learn from big data and learn from it, and we can think in its way, but don't be obsessed with big data. 5 Where is the bottleneck of innovative enterprises in the era of big data? Is it a talent problem or a user privacy problem or a data access channel problem? "For startups, big data should have a small application, and this small application should be a successful application, not trying to be a big application. Using big data to do big application is not something startup-type companies do, to think about how this application and the final profit model directly hooked. " Tang Jun: big data, big data, there is not enough data volume is actually not constructed big data, it is also difficult to make a just said since this kind of judgment or decision-making, so all is based on the premise of big data, but for our general startup companies, they are difficult to collect enough data, like Google before it is possible to collect so much big data. data. Therefore, the problem of data acquisition channels is a big bottleneck. Ding Zuyu: I think it is the data application, I think the bottleneck now, the first three aspects are really some problems, but in fact they have thought of a way, such as the problem of talent, can be on their own, the problem of user privacy, now there is nothing privacy, and then the database, anyway, they have their own channels, only today it is also not called big data only, we can use a big data hat to it up! But I think in fact for startups, big data should have a small application, this small application is what we think is a successful application, and do not want to be a big application, with big data to do big application is not a startup company to do things, but this application, today and business or the final profit model can be directly linked, I think this is the biggest problem for all startups! I think this is the biggest challenge for all startups. Shaofeng Zhang: I choose the talent, why? It is because I have been doing data mining for ten years, and I knew when I was working at IBM that a data warehouse is particularly prone to failure, that is, the technical staff say technical words, and the business staff say business words. In the end is the need for a technical thinking, but also business thinking business model talent, this person is very difficult to find, you go to talk to your customers a bunch of, I can help you deal with the data, deal with the data to do what ah? Do not speak clearly, this I think is a bottleneck to limit the development of startups, this piece to be very comprehensive thinking people, this is not very good to master, this is one of my views. Chai Ke: I also think it is a talent problem, we now have professional gynecologists in the team, but far from enough, especially like gynecologists, we put its salary of 300,000 yuan per year to 600,000 yuan per year, no one is willing to come, first, because not too trusting of small companies, you are in a start-up organization, he is in the hospital, very stable, stable, and the second is because of the general experience of these doctors, are older, so the medical experience is very good, but not enough. doctors, are older, so he is more after stability. And then there's the fact that he doesn't care about Internet stuff, so I think people are a challenge at least in our business. Zhang Yiming: I think the bottleneck is the product, because I think the talent, privacy bottom line, data channels are really a problem, but the problem is not necessarily a bottleneck, because I just said that with the product, to provide a very good product will have a lot of user data, there will be a channel of access to data, a good product, good data, to build a good platform, the talent he will come, not to say that you pull out of the very top organizations of very good Talent pull out, the problem is solved, it has to have a good product to attract him to make a big difference in the product. For example, Google is acquiring a company called WAZE (crowdsourcing maps), he is a small startup, he is all for one and one for all, through their own applications to collect a large amount of data, Google and facebook, the two big companies are grabbing the data of this startup, which is a very good example. The way you collect data has to be unique and provide an application, which is the product.