Today, when big data has become a trend and a national strategy, how to maximize the value of big data has become a question that people are thinking about. Whether it is 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 will be able to seize the market and win development. While exploring big data business models, big data is accelerating its application in all walks of life. Big data not only helps people with shopping, traveling, and making friends, but also plays a role in important events such as college entrance examinations.
The big data industry has the characteristics of non-pollution, eco-friendly, low investment and high added value. It is very important for our country to transform the past resource-based economic growth model, promote the "Internet +" action plan, and realize the 30-year development of the national manufacturing industry. Goals are strategic. In the past few years, the domestic big data industry has been discussed more and implemented less, and the business model is in the initial exploration stage. The industry is in two extremes: one is that overheated impetuousness has brought certain bubbles and industry risks; the other is doubts about big data. It’s just hype and still adheres to traditional management concepts and business models. But after entering 2015, the big data industry bid farewell to the bubble and entered a more pragmatic development stage, moving from the nascent stage of the industry to the growth stage. Currently, how to monetize big data has become an important direction for the industry to explore.
B2B Big Data Exchange
Both domestic and foreign companies are promoting big data transactions. Currently, our country is exploring a B2B big data exchange model with a “national team” nature.
On February 20, 2014, the Zhongguancun Big Data Trading Industry Alliance, China’s first industrial organization for data trading, was established. On the same day, the Zhongguancun Shuhai Big Data Trading Platform was launched to position itself as a big data trading service platform. . On April 15, 2015, Guiyang Big Data Exchange was officially launched and completed its first batch of big data transactions. The sellers of the first batch of data transactions completed by Guiyang Big Data Exchange were Shenzhen Tencent Computer Systems Co., Ltd. and Guangdong Digital Guangdong Research Institute, and the buyers were JD Cloud Platform and CICC Data Systems Co., Ltd. On May 26, 2015, at the 2015 Guiyang International Big Data Industry Expo and the Global Big Data Era Guiyang Summit, Guiyang Big Data Exchange launched the "2015 China Big Data Trading White Paper" and the "Guiyang Big Data Exchange 702 Convention". It points out the direction for the nature, purpose, transaction objects, information privacy protection, etc. of big data exchanges, and lays the industrial foundation for the realization of big data gold mines.
Consulting Research Reports
Most of the data in domestic consulting reports come from the statistical data of various ministries and commissions such as the National Bureau of Statistics. Professional researchers analyze and mine the data to identify various industries. The quantitative characteristics are then used to draw qualitative conclusions, which are often found in "Market Research Analysis and Development Consulting Reports", such as "Market Research Analysis and Development Consulting Reports on China's Communications Equipment Industry from 2015 to 2020", "Sales Status of China's Mobile Phone Industry from 2015 to 2020" Analysis and Development Strategies", "2015 Optical Fiber Market Analysis Report", etc. These consulting reports are for social sales and are actually the big data transaction model of O2O.
Analytical reports from all walks of life provide a large number of companies in the industry with data references for intellectual achievements, corporate operations and marketing, which is conducive to the market optimizing the supply chain, avoiding overcapacity and maintaining market stability. These are professional studies based on structured and unstructured data from the statistics department. This is the traditional one-to-many industry big data business model.
Data mining cloud computing software
The emergence of cloud computing provides a cheap solution for small and medium-sized enterprises to analyze massive data. The SaaS model 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.
Experts in the industry have pointed out that big data = massive data + analysis software + mining process. Providing diverse data mining services through powerful analysis software with different strengths is its profit model. Domestic big data companies have developed these big data analysis software based on the cloud: it integrates statistical analysis, data mining and business intelligence. Users only need to import data into the platform to take advantage of the rich algorithms and algorithms provided by the platform. Model, perform data processing, basic statistics, advanced statistics, data mining, data mapping and result output, etc. Data is managed uniformly by the system, which can distinguish private and public data, ensuring that private data can only be used by the holder. It also supports access to multiple data sources and is suitable for analyzing data from all walks of life. It is 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 their own models for secondary development.
Big data consulting and analysis services
The larger the scale of institutions and companies, the greater the amount of data they have, but few companies have their own big data analysis like large Internet companies. team, so there must be some professional big data consulting companies. These companies provide big data modeling, big data analysis, business model transformation, marketing planning, etc. based on management consulting. With big data as a basis, the consulting company’s conclusions and consulting results 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 once said in public that big data can save 60% of agricultural input in Guizhou while increasing output by 80%. The company's ability to make such a conclusion is of course based on its accumulation of Guizhou's agricultural, weather, soil and other data and its modeling and analysis capabilities.
Government Decision-making Advisory Think Tank
The "Decision of the Central Committee of the Communist Party of China on Several Major Issues Concerning Comprehensively Deepening Reform" passed by the Third Plenary Session of the 18th CPC Central Committee clearly stated that strengthening the Build new think tanks and establish and improve decision-making consultation systems. This is the first time that the concept of "think tank" has been proposed in the central document of the Communist Party of China.
In recent years, a number of think tanks oriented towards building modern think tanks and aiming to serve the national development strategy have been rapidly established. The number of think tanks in China has jumped from 12th in the world in 2008 to 2nd currently. Big data is the core of think tanks. Without data, the predictions and analyzes of think tanks will be like water without a source. In the case of massive or even flooding of information, think tanks must rely on big data analysis to improve their ability to sort out and integrate information.
Research believes that 93% of behaviors are predictable. If events are digitized, formulated, and modeled, in fact, no matter how complex the event is, there are predictable rules to follow, and the development direction of the situation is Extremely predictable. It can be seen that the application of big data will continue to improve the government's decision-making efficiency and scientific decision-making.
Big data analysis on own platform
As the value of big data is 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. Analyze big data and embed it into the enterprise's internal ERP system information flow. The data guides the enterprise's internal decision-making, operations, cash flow management, market development, etc., and plays a role in adding value to the enterprise's internal value chain.
In the era of Analytics 1.0, data warehouse is regarded as the foundation of analysis. In the 2.0 era, companies mainly relied on Hadoop clusters and NoSQL databases. New "agile" analysis methods and machine learning technologies in the 3.0 era are providing analysis results at a faster speed. More companies will set up chief analytics officers in their strategic departments and organize cross-departmental, cross-disciplinary personnel with rich knowledge structures and rich marketing experience to conduct hybrid analysis of various types of data.
Big data investment tools
Securities market behavior and various indices are closely related to investors’ analysis, judgment and emotions. In 2002, the Nobel Prize in Economics was awarded to behavioral economist Kahneman and experimental economist Smith. Behavioral economics began to be accepted by mainstream economics. 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, netizen user emotions, investment behaviors and stock prices. They study Internet behavioral data, pay attention to hot topics and market sentiment, and dynamically adjust investment portfolios. , and developed big data investment tools, such as big data funds, etc. These investment tools directly transform big data into investment and financial products.
Directed Procurement Online Trading Platform
Data analysis results are often the business basis for 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 now, but for virtual commodities such as data, there is currently no specific online trading platform. For example, if a clothing manufacturing company targets the market in a certain province and needs the median and average data on the height and weight of customers in that market, then hospital physical examination departments and professional physical examination institutions are the suppliers of these data. By obtaining this data, clothing companies will be able to carry out refined production and produce clothing that meets market demand at a lower cost. Imagine if there was such a "big data directional procurement platform", just like Taobao shopping, it can initiate buyer demands and launch seller products. Through this model, plus a third-party payment platform, "data analysis conclusions" such Commodities will emerge quietly. Such commodities do not occupy logistics resources, do not pollute the environment, and respond quickly, but they have a huge market for both "supply" and "demand". Moreover, basic data security can be ensured through this platform. What the big data directional procurement service platform trades is not the underlying basic data, but the data results obtained through cleaning and modeling. All sellers and buyers must have real-name authentication, establish an integrity file mechanism, and be connected to the national credit system.
Non-profit data credit evaluation agency
Before the country incorporated the protection of citizens’ information into the scope of criminal law, citizens’ personal information was often sold publicly at a clear price, forming a “grey industry” ". To this end, the Criminal Law Amendment (VII) passed on February 28, 2009 added the crime of selling or illegally providing citizens’ personal information, and illegally obtaining citizens’ personal information. This law specifically refers to staff of state agencies or financial, telecommunications, transportation, education, medical and other units who are not allowed to 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. Scam calls, harassing calls, and sales calls not only increase the traffic of operators, but also undermine the credit system of the entire society and citizens. sense of security.
Although data trading was previously cleaned data stipulated by the exchange, exchange employees were essentially unable to monitor the massive data across the country. Data cleaning only cleans data that does not meet the format requirements. There are three main categories: incomplete data, erroneous data, and duplicate data. Therefore, it is very necessary to establish a non-profit data credit evaluation agency and integrate data credit into the corporate and personal credit systems as part of the national credit system to prevent black market transactions from becoming normal market behavior.
In addition to credit evaluation agencies, in the future, the national public security department may establish a data security bureau, which will be included in the scope of the Internet police and focus on cracking down on basic data that infringes on corporate business secrets and citizen privacy. The act of trafficking.
Conclusion:
Big data has gradually moved from forums and impetuous perspectives to national governance system construction, marketing management, production management, securities markets, etc., and its business models are also diverse. Variety. Market experience shows that as long as there is buying and selling, there will be a commodity economy, and which business model will be the mainstream will be determined by the market. The final facts will prove that the big data trading commodity economy will inevitably become an important part of "Internet +".