Tao was first put forward by Laozi, "Tao can be Tao, but it is extraordinary;" Ming Can is bright, very bright ",which means to follow the laws of nature. As the name implies, the way of big data is to find out the rules in big data.

At present, with the in-depth development of the era of big data, people's understanding of big data is gradually deepening. Big data mainly includes the following aspects: first, data collection, second, data storage, third, data parallel computing, fourth, analysis and mining of big data, fifth, display of big data, and sixth, privacy protection and legal issues of big data. Not long ago, at the CIO conference held in Xining, Qinghai Province on 20 17, Gong Caichun, the founder of Vocational Products Exchange (formerly the chief scientist of Dajie.com), said in his speech: "In the analysis and mining of big data, there has never been a universal model that can analyze the value of our data in any scenario. There is no such big data product now, and I believe there will be no such product for a long time to come. In other words, it is impossible to make the analysis and mining of big data into a universal product. But what do big data analysis and mining have in common? We call this common thing "the road of big data". "In order to explain the true meaning of big data, Dr. Gong Caichun has mentioned the meanings of kingly way, imperial way and overbearing. From Huangdi to Yaoshun, to Shang Yang, to today's rule of law, it reflects the historical changes and evolution of Western Europe from kingly way to overbearing. In the world of big data, what are kings, emperors and hegemony? As Dr. Gong said: "The hegemony of big data companies is numbers. When you can think of data in any situation, you may solve your problem in a short, flat and fast way. The king of big data is data. You should accumulate data, analyze data and mine data. This is what we call the king of big data. If the company wants to continue to develop, mathematics is the emperor of big data. A problem is fundamentally solved only if it is solved by mathematical methods. So my conclusion is that the overlord of big data is numbers, the king of big data is data, and the emperor of big data is mathematics. "Numbers: the hegemony of big data In the era of big data, when enterprises attribute all the problems they face to a single number, they can easily find problems and solve them. For example, the well-known Oscar Award and Hurun Report, the Oscar Award is to select the best movies from 24 items in the world, and good or bad ultimately comes down to a digital quotient. In the same way, so is Hurun's ranking. Let's describe how much money people all over the world have, turn this money into a number and rank this number. At present, the same is true of professional product exchanges: personal performance in the workplace, personal Excellence and reputation are all expressed by a number, and a person's credit problem is turned into a simple number, no matter how wide the person's network is, how strong his ability is and how great his achievements are, it is best to turn it into a number. When you turn all the questions into numbers and calculate this number, you will find that you have accomplished a very important job when using big data. Especially in the workplace, you need to face all kinds of numbers, and when HR looks at a person, it only needs to look at the number of this person's one-dimensional quotient. When you make a big data item, you will eventually boil it down to a few numbers, then you are close to half the success. This is the hegemony of big data. Data: The King of Big Data In the era of big data, people need to make some changes in their concepts and ways of thinking. We need to have two consciousnesses: First, we should put ourselves in other's shoes. In the era of small data, we should pay attention to sampling. In the era of big data, sampling has been eliminated. Not only do we not need to take samples, but we should use the same method. When collecting data, we will collect all the data and cannot clean it. The second is fault-tolerant thinking. Fault-tolerant thinking corresponds to small data, that is, to clean the data, which may be inaccurate, inaccurate or even wrong. Therefore, finding ways to get rid of it is a common practice in the era of small data. Although it was also done in the era of big data, it is necessary to find out the reasons and reasons of data errors in a different way while clearing the wrong data. When you are in the era of big data, as long as there are two different scenarios, the data you need is completely different. So in the era of big data, there is no need to delete any data, which is called fault-tolerant thinking. Mathematics: The Emperor of Big Data In the era of big data, enterprises or individuals use mathematical models to express the problems they face, thus solving the problems they face. This is the big data emperor. Job-hopping is to judge whether a resume is true and personal credit rating through a series of mathematical models. If judging by establishing a mathematical model, Dr. Gong Caichun also takes the ranking of China University as an example: "If I want to prove to others that I am a Ph.D. in Computing of Chinese Academy of Sciences, the easiest thing is to show you my thesis, and everyone will know that I am really a Ph.D. in Computing of Chinese Academy of Sciences. This is the material submitted by myself. Of course, there are various ways to demonstrate it. Here's how we calculate a person's math score and how his work score is 905. This needs calculation, and there is a calculation model. This is my personal experience. I am studying for a master's degree in Shandong University. Why should I go to Chinese Academy of Sciences from Shandong University? Personally, I think Chinese Academy of Sciences is better than Shandong University. After these calculations, a directed graph is formed. We have1.50 billion resumes, of which more than 2,000 resumes are from one school to another. There are only 3,000 schools in China. This map is very dense and easy to analyze and mine. After we formed such a directed graph, we analyzed and mined it. This analysis mining algorithm can refer to Google's algorithm. Through some column pair calculations, we can figure out which university in China is the best, and the university ranking is like this. "China company's ranking. There are 80 million companies in China, which is the best? It can be calculated by mathematical model: there are 920 million employees in China, and their credit scores can be calculated to produce an iterative calculation model. Generally speaking, excellent employees will enter excellent companies. In addition, an individual's credit status also depends on what kind of friends his friends are, that is to say, an individual's credit status is equal to the average of a friend's credit status, so as to establish a mathematical analysis model, and through iterative model calculation, we can calculate who is the best company in China. Conclusion: In a word, whether it is the kingly way of big data, hegemony or emperor Wang Zhidao, in the final analysis, it is necessary to collect, mine, analyze and sort out big data. The essence of big data is not the data itself, but the effective analysis and application of data, and the real meaning of big data is "correct data". Collecting scattered numbers into data, and then establishing a mathematical model to analyze and apply the sorted data, this is the true meaning of big data from bullying to kingliness, and it is also the earliest realization of kingliness. In the future, with the development of the era of big data, big data will surely become an indispensable tool for enterprise development. How to achieve the ultimate goal of big data is a problem that enterprises should consider.