The vending machine industry how to out of the set set theory

No condom vending machine industry theory is actually concept of logic, after being famous economist, even when walking into the economic study. Mean, some remarks are in any case can't be wrong, but essentially these theory is vague, but it didn't have any actual content, but cannot deny the importance of it. Because plus some standard conditions, the narrowing the scope of these theories, it will play a guiding role in reality. This is why a lot of people hear in the Internet age concept, conformity and yourself to do and think it's too vague, no use, is their understanding and cognitive deviation, walked into the set set theory of myth. Any theory, any concept at the time of use, are conditions, it is not necessarily suitable for all sectors, all businesses, all of us. A need to distinguish between the direction of industry of thinking, to distinguish the specific business environment, otherwise it is easy to fall into trap set set theory. How much is this set set the vending machine industry theory, without any effect? Can definitely say that many, many, many, and many are propped up by the Internet and electronic business leaders. It is necessary to understand what the true meanings of these theories, the electricity, the Internet should be a real industry, rather than every year to blow a bubble, let a group of people to chase. Popular point, the vending machine industry big data is a feature of the Internet development to today is to use a new type of technology, cloud computing, etc. , will be difficult to set up the enormous data extraction and analysis before, into the analysis of the unity, unified value classification, the business in order to have a more precise guidance. Different from previous sampling analysis to the value of the sample analysis instead of the value of the whole data, its treatment and results on decommissioning precision than the traditional way. 。 So, what kind of the vending machine enterprises need big data? It can be said that all business activities need the guidance of the large data, it is meaningful to the business. But there is a big difference from real implementation and theory, the first is the value of the data: classification accuracy enough, have you done segment, to know what kind of enterprises under what circumstances can use the data as a reference. Just know big data is very good, all the business can use big data to analyze, in accordance with the decision making, it is not enough. There is a problem, is to use the vending machine industry data to make decisions and use experience to make decisions, which is more important? It makes me think of the story: how to recognize which is the empty box on production line, the probability is very small, it is must solve the problem, research funding may be huge, developed the laser sweep trace to identify; Older workers can also put a fan on the production line of the conveyor belt, the empty box blown away, dozens of yuan can solve the problem. This time is that we want to consider efficiency, rather than blindly worship the vending machine industry of big data, data only. In reality, we have a lot of people did, in the process of chasing, worship of all new theory, the case for success as a trend. Believe that professional organizations data analysis results, the predicted business trends. 。 If you really want to reason and make big data, ordinary people are speaking but, for he had ten thousand reasons to convince you, let you believe that out of the big data, is difficult. When you made a determined heart with big data management enterprise, but found a hindrance, broad and talk, struggling in actual application. You will find that the need is some simple statistics, simple data analysis, and is not profound deduction and multi-dimensional data analysis. For example, we want to do a simple data analysis, analysis of a large electric business platform for the evaluation of an industry authenticity, user preferences, etc. , thus deduced the trend of the next year, or what kind of products more popular now. The results after coming out, may be quite different from the real situation. This is because the data source has a lot of difficult to distinguish between things, users can't control the actual circumstances of the data source. Brush like shopping evaluation, there may be a single, exist cashback, exist because users are not satisfied with unwillingness to evaluate and well received by default, and because there is no strong preference for a long time people used to praise these reasons are likely to influence