The so-called big data refers to the amount of information involved is so large that it can not be achieved through the current mainstream software tools, in a reasonable period of time to capture, manage, process, and organize the information to help customers make decisions for a more positive purpose; Victor pointed out in the "era of big data," the advent of the era of big data so that for the first time human beings have the opportunity and the conditions in a very large number of fields and a very in-depth level of access to and the use of comprehensive data, complete data, and systematic data, to acquire knowledge that was previously impossible to acquire. Big Data has three concepts different from the previous ones - "correlation thinking, whole data, and mixed thinking", i.e., Big Data emphasizes correlation thinking instead of causal thinking, and pays attention to whole data instead of focusing on random cases, and its thinking emphasizes mixed thinking instead of precise thinking. Its thinking also emphasizes mixed thinking rather than precise thinking. At present, the collection and evaluation of cadres' information emphasize on sample, source and accuracy, the channel is relatively single and the amount of information is small, the result often cannot reflect the situation of a cadre in a comprehensive way, which leads to cadres' "promotion with disease" or incompetence of their duties occasionally occur. Personally, I believe that the concept of big data and modern information technology, the establishment of a comprehensive examination and assessment of cadres of information collection and evaluation of the use of the system, that is, cause and effect thinking and correlation of thinking to go hand in hand, the focus on random samples and the discovery of the use of all the data to be integrated and balanced, not only accustomed to using fine thinking should be used also accustomed to using chaotic thinking. Nowadays, whether in academia or IT circles, people have been discussing big data, however, big data analytics, big data marketing, etc. are just getting started, so why is big data important to us? Business organizations use relevant data and analytics to help them reduce costs, improve efficiency, develop new products, make more informed business decisions, and more. For example, by combining Big Data and high-performance analytics, all of the following could be beneficial to a business:Parsing the root causes of failures, problems, and defects in a timely manner could potentially save a business billions of dollars each year. Plan real-time traffic routes for thousands of delivery vehicles to avoid congestion. Analyze all SKUs to price and clear inventory with the goal of maximizing profits. Push offers to a customer that he might be interested in based on his buying habits. Quickly identify gold medal customers from a large number of customers. Use clickstream analytics and data mining to circumvent fraud. In short, the value that big data plays on the fine operation of enterprises is very great, which can make the operation of enterprises on social platforms more perfect, try to make enterprises have an ideal reputation, and do public opinion monitoring of some bad remarks, etc., and then make product improvement according to the data, and the use of big data can also better drive the user experience, and promote the enterprise's operation goals in the right direction, which are the value that big This is the value that big data brings to enterprises. The first disciplines to propose the concept of big data were astronomy and genetics, which have relied on analytical methods based on massive amounts of data since their inception. Big Data can be said to be the product of the combination of computers and the Internet, computers realize the digitalization of data; the Internet realizes the network of data; the combination of the two is what gives life to Big Data! With the ubiquitous penetration of the Internet into our work and life as air, water and electricity, coupled with the popularization of mobile Internet, Internet of Things, wearable networking devices, new data is being generated at an exponential rate of acceleration. It is said that 90% of the world's current data was generated rapidly after the emergence of the Internet. However, putting aside the surface phenomenon of quantitative production and storage of data, we should pay more attention to the qualitative changes brought about by the quantitative changes in data, which are manifested in the following three aspects: the era of big data brings us a brand new way of thinking, and changes in the way of thinking in the next generation to become the mainstay of social production will bring about disruptive changes in the industry! - Focus on the complexity of the data, weakening the accuracy; - Focus on the relevance of the data, rather than causality. Historically, business change is the beginning of a change in mindset, the old economic system and traditional business concepts facing the logic of the new business thinking, if the brain can not keep pace with the times, absorbing and transformed into a new thinking to meet the trend, through the new thinking to re-organize the business organization's strategy, structure, culture and a variety of tactics, then seemingly strong body instead of becoming a liability for the enterprise to move forward. This new thinking subverted the giant case first occurred in the traditional field of information technology, and then penetrated into the traditional business field: Blackberry (Blackberry), Motorola, Nokia, Kodak, Yahoo! Cases abound! Of course, the decline of these companies is not due to the lack of data thinking, but they are all former giants eliminated by the new Internet thinking. Data thinking is the latest thinking, and its influence has not yet grown to the point of causing giants to come crashing down. However, if it is not given enough attention, you may be on the list of the next wave of fallen kingdoms! In the era of big data, we need more comprehensive data to improve the accuracy of analysis (prediction), so we need more cheap, convenient and automatic data production tools. In addition to all kinds of personal information data we leave behind intentionally or unintentionally using browsers and software in the virtual world of the Internet, we are producing data with a variety of wearable digital products such as cell phones, smart watches, smart bracelets, smart necklaces, etc.; our home routers, televisions, air-conditioners, refrigerators, drinking fountains, vacuum cleaners, smart toys, etc. are also starting to become more and more intelligent and have the function of networking, and these These household appliances are producing a lot of data while serving us better; even when we go out shopping, the routers of merchants, the WLAN and 3G of carriers, the ubiquitous cameras and electronic eyes, the self-service screens of department stores, the ATMs of banks, gas stations, and the credit card machines of various convenience stores are all collecting and producing data. In the Internet field, we like to say the word entrance, the entrance corresponds to the direct meaning of the traffic, and the traffic in the Internet field means money, this traffic realization may be advertising, may be the game, may be e-commerce. In the era of big data, the word "entrance" also has a more profound meaning, that is, the source of data production, the user through an APP or hardware products to meet certain needs of colleagues, will also leave a series of related data, the reasonable use of these data can make the enterprise with this part of the data to obtain greater commercial interests! Therefore, in the era of big data, companies that realize that data is also an asset have begun to lay out in the various sources of data production, which may be a WEB site that solves the needs of just emerging, or a simple tool APP, or a wearable digital product! With data assets, it is necessary to mine the value of the assets through analysis, and then realize them into user value, shareholder value and even social value. The core purpose of big data analytics is prediction, based on massive data, various techniques related to machine learning and mathematical modeling are used to predict the likelihood of things happening and take corresponding measures. Predicting stock prices, predicting airfare, predicting the flu, and so on. Predicting the likelihood of things happening continues down the line, and appropriate interventions can be made to steer things in the desired direction. For example, Amazon, like all e-commerce companies, will be based on the analysis of the user's preferences and spending power to recommend goods, guiding the user to increase the amount of consumption; Google and other Internet giants will also be through a variety of technological means to try to show different ads to different users, and is called precision marketing, which improves the click-through rate (the company's revenues); online gaming companies will also be in the operation of the project through the analysis of the player's behavioral The data is analyzed to make timely adjustments to the design of game levels and billing points.