What business applications are still valid in the data warehouse even if they have expired data?

today, with big data becoming a trend and a national strategy, how to maximize the value of big data has become a question for people to think about. Whether for Internet companies, telecom operators or a large number of start-ups, the realization of big data is particularly important. Whoever finds the password first can seize the market and win development. While exploring the business model of big data, big data is accelerating its application in all walks of life. Big data not only helps people to shop, travel and make friends, but also plays a role in such important events as the college entrance examination. Big data industry has the characteristics of pollution-free, eco-friendly, low input and high added value, which is of strategic significance for China to change the past resource-based economic growth mode, promote the "internet plus" action plan and realize the 3-year development goal of the national manufacturing industry. A few years ago, the domestic big data industry was discussed more and landed less, the business model was in the initial stage, and the industry was at two extremes: one was that overheated impetuousness brought certain bubbles and industrial risks; One is to suspect that big data is just hype and still adhere to traditional management concepts and business models. However, after entering 215, the big data industry bid farewell to the bubble, entered a more pragmatic development stage, and entered a growth period from the embryonic stage of the industry. At present, how to realize big data has become an important direction for the industry to explore. B2B Big Data Exchange Enterprises at home and abroad are promoting big data transactions. At present, China is exploring the "national team" B2B big data exchange model. On February 2th, 214, Zhongguancun Big Data Trading Industry Alliance, the first industrial organization facing data trading in China, was established. On the same day, Zhongguancun Digital Big Data Trading Platform was launched to locate the trading service platform of big data. On April 15th, 215, Guiyang Big Data Exchange was officially put into operation and completed the first batch of big data transactions. The sellers of the first batch of data transactions completed by Guiyang Big Data Exchange are Shenzhen Tencent Computer System Co., Ltd. and Guangdong Digital Guangdong Research Institute, and the buyers are jingdong cloud Platform and Zhongjin Data System Co., Ltd. On May 26th, 215, at Guiyang International Big Data Industry Expo 215 and Guiyang Summit of Global Big Data Era, Guiyang Big Data Exchange launched the White Paper on China's Big Data Trading in 215 and the Convention of Guiyang Big Data Exchange 72, which pointed out the direction for the nature, purpose, transaction object and information privacy protection of big data exchanges and laid the industrial foundation for realizing big data gold mines. Consulting Research Report Most of the data of domestic consulting reports come from the statistical data of the National Bureau of Statistics and other ministries and commissions. Professional researchers analyze and mine the data to find out the quantitative characteristics of various industries and then draw qualitative conclusions, which are common in "market research analysis and development consulting reports". For example, "China Communication Equipment Industry Market Survey and Analysis and Development Consultation Report from 215 to 22", "China Mobile Phone Industry Sales Situation Analysis and Development Strategy from 215 to 22" and "Optical Fiber Market Analysis Report in 215", etc. These consultation reports are for social sales, which is actually the big data trading mode of O2O. The analysis reports from all walks of life provide a large number of enterprises in the industry with data reference on intellectual achievements, enterprise operation and marketing, which is conducive to optimizing the supply chain, avoiding overcapacity and maintaining market stability. These are professional studies based on the structured data and unstructured data of statistical departments, which is the traditional one-to-many industry big data business model. The emergence of data mining cloud computing software cloud computing provides a cheap solution for small and medium-sized enterprises to analyze massive data, and SaaS mode is the greatest charm of cloud computing. SaaS software in cloud computing services can provide third-party software and plug-ins for data mining and data cleaning. Some experts in the industry have pointed out that big data = massive data+analysis software+mining process, and providing diverse data mining services through powerful analysis software is its profit model. Some big data companies in China have developed these big data analysis software based on cloud: it integrates statistical analysis, data mining and business intelligence. Users only need to import data into the platform, and they can use the rich algorithms and models provided by the platform to carry out data processing, basic statistics, advanced statistics, data mining, data mapping and result output. The data is managed by the system in a unified way, which can distinguish private data from public data, ensure that private data is only used by holders, and support access to various data sources. It is suitable for analyzing data from all walks of life, easy to learn and use, and the operation interface is simple and intuitive. Ordinary users can use it with a little understanding, and it is also suitable for high-end users to model themselves for secondary development. The bigger the big data consulting and analysis service organizations and enterprises are, the more data they have. However, few enterprises have their own big data analysis teams like large Internet companies, so there must be some professional big data consulting companies that provide big data modeling, big data analysis, business model transformation and marketing planning based on management consulting. With big data as the basis, the conclusions and consulting results of consulting companies are more convincing, which is also the transformation direction of traditional consulting companies. For example, the vice president of a large foreign IT research and consulting company has said in public that big data can save 6% of investment and increase 8% of output in Guizhou agriculture. Of course, the company can make such an assertion based on its accumulated data on agriculture, weather and soil in Guizhou and its modeling and analysis ability. The Decision of the Central Committee on Several Major Issues of Comprehensively Deepening Reform, which was adopted by the Third Plenary Session of the 18th CPC Central Committee, clearly proposed to strengthen the construction of new think tanks with China characteristics and establish and improve the decision-making consultation system. This is the first time that the central document of China has put forward the concept of "think tank". In recent years, a number of think tanks oriented to building a modern think tank and aiming at serving the national development strategy have been established rapidly. The number of think tanks in China has jumped from the 12th in the world in 28 to the 2nd at present. Big data is the core of think tanks. Without data, the prediction and analysis of think tanks will be passive water. In the case of massive information or even flooding, think tanks must rely on big data analysis to improve their ability to sort out and integrate information. The research shows that 93% of behaviors are predictable. If events are digitized, formulated and modeled, in fact, how complicated events have predictable laws to follow, and the development trend of events is extremely predictable. It can be seen that the application of big data will continuously improve the efficiency and scientific decision-making of the government. With the value of big data being gradually recognized by all walks of life, large and medium-sized enterprises with a large customer base have also begun to develop and build their own platforms to analyze big data, which are embedded in the information flow of ERP systems within enterprises, and the data will guide the internal decision-making, operation, cash flow management, market development, etc., and play a role in increasing the value chain within enterprises. In the era of analysis 1., data warehouse is regarded as the basis of analysis. In the 2. era, the company mainly relied on Hadoop cluster and NoSQL database. The new "agile" analysis method and machine learning technology in the 3. era are providing analysis results at a faster speed. The company will set up a chief analyst in its strategic department, and organize people with rich knowledge structure and marketing experience to conduct mixed analysis of various types of data. The securities market behavior and various indexes of big data investment tools have a great relationship with investors' analysis, judgment and emotions. In 22, the Nobel Prize in Economics was awarded to behavioral economist Kahneman and experimental economist Smith. Behavioral economics began to be accepted by mainstream economics, and behavioral finance theory integrated psychology, especially behavioral science theory, into finance. In real life, Internet companies with a large amount of user data connect their forums, blogs, news reports, articles, netizens' user emotions and investment behaviors with the stock market, study the behavior data of the Internet, pay attention to hot spots and market emotions, dynamically adjust their investment portfolios, and develop big data investment tools, such as big data funds. These investment tools directly transform big data into investment and wealth management products. The data analysis results of online trading platform for directional procurement are often the business foundation of other industries. At present, the e-commerce of the real economy in China has achieved B2C, C2C, B2B, etc., and even O2O is becoming more and more popular. However, there is no specific online trading platform for virtual goods such as data. For example, garment manufacturing enterprises need the median and average data of the height and weight of customers in a certain province's market, so hospital physical examination departments and professional physical examination institutions are the suppliers of these data. By obtaining these data, garment enterprises will be able to carry out fine production and produce garments that meet the market demand at a lower cost. Imagine that if there is such a "big data oriented procurement platform", just like Taobao shopping, it can launch buyers' demand and sellers' products. Through this model and a third-party payment platform, the commodity "data analysis conclusion" will emerge quietly. This commodity does not occupy logistics resources, does not pollute the environment and responds quickly, but it has a huge market for both "supply" and "demand". Moreover, through this platform, the security of basic data can be guaranteed. The big data-oriented procurement service platform trades not the underlying basic data, but the data results modeled through cleaning. All sellers and buyers should have real-name authentication, establish a credit file mechanism and connect with the national credit system. Before the protection of citizens' information was brought into the scope of criminal law by non-profit data credit evaluation institutions, citizens' personal information was often sold publicly at a clearly marked price, and a "gray industry" was formed. Therefore, the crime of selling and illegally providing citizens' personal information and the crime of illegally obtaining citizens' personal information were added to the Criminal Law Amendment (VII) passed on February 28, 29. The law specifically refers to the staff of state organs or financial, telecommunications, transportation, education, medical and other units, and may not sell or illegally provide citizens' personal information to others. However, citizens' information is still being sold in various examination agencies, real estate agencies, phishing websites and website forums. Fraudulent calls, harassing calls and sales calls are not only increasing the operator's telephone traffic, but also undermining the credit system of the whole society and citizens' sense of security. Although the data was cleaned by the exchange before the transaction, the exchange staff could not monitor the massive data of the whole country in essence. Data cleaning only cleans the data that does not meet the format requirements, which mainly includes incomplete data, incorrect data and repeated data. Therefore, it is very necessary to establish a non-profit data credit evaluation institution. As a part of the national credit information system, it is necessary to incorporate data credit information into the enterprise and individual credit information system to prevent black market transactions from becoming the normal behavior of the market. In addition to credit rating agencies, the national public security department may set up a data security bureau in the future, which will be included in the category of network police, focusing on cracking down on the behavior of selling basic data that infringes on business secrets and citizens' privacy. Conclusion: Big data has gradually moved from the forum to the national governance system construction, marketing management, production management, securities market and other aspects, and its business models are also diverse. Market experience shows that there is a commodity economy when there is buying and selling, and the specific business model will be determined by the market. The final facts will prove that the commodity economy of big data trading will inevitably become an important part of the "internet plus".