The business of big data is actually very simple, that is, income increases and expenses decrease; It is to increase customers, improve customer experience and increase the leverage ratio of capital return; After the application of big data matures, big data can predict the business future and discover new business opportunities.

A stone stirs up a thousand waves. Document No.201550 "Action Plan for Promoting the Development of Big Data" issued by the State Council has filled the circle of friends, especially referring to vigorously promoting data sharing among government departments and steadily promoting the opening of public data resources. By the end of 20 17, cross-departmental data resources will be shared, and by 20 18, the unified platform will be fully covered and data will be shared and exchanged. In 2020, cultivate 10 international leading big data core leading enterprises and 500 big data application, service and product manufacturing enterprises.

As we all know, big data has great commercial value. However, the commercial value of big data in China has not been fully tapped. The main difficulty lies in the decentralization of big data, and most valuable data is concentrated in the hands of the government, monopoly enterprises and Internet giants. Decentralized data cannot help enterprises to obtain valuable information and realize the commercial realization of big data. The government's opening up data and establishing a big data trading market are the top priorities of the application of big data business value in China.

In addition, the application scenarios and privacy issues of big data are also two major problems in the commercial application functions of big data. If you don't understand the application scenarios of big data, you can't find valuable data and you can't make it work. The application of big data will stay in the low-level stage of the era of data collection, processing and storage, unable to realize the commercial realization of big data, prompting enterprises to further invest in big data and form an ecological cycle of data value application. The privacy of big data is an unavoidable problem for all enterprises. What kind of data can be exchanged, collected and realized as commodities and circulated in the market? These problems not only affect the protection of personal privacy, the enthusiasm of enterprises to buy data products, but also affect the development of data enterprises.

Big data enterprises in China are divided into three categories. One is big data technology companies, which provide enterprises with big data platform construction, technical consultation, big data computing and storage products, such as Huawei, AsiaInfo, Inspur and other traditional IT companies. One is a big data service company that provides services, platforms and products based on big data technology for enterprises. Including building big data processing platforms such as big data mining tools, search engines and analysis engines for enterprises, and cleaning and mining services such as Luo Ming Science and Technology, ADMaster and Percent. The last category is big data companies that provide data products. They own data, process and generate valuable data, and provide standard data products for the market. For example, Sesame Credit, TalkingData, Ninth Force, and Star Map Data.

There are four data sources in China's big data market. One is the external data collected by web crawler, and most companies that provide public opinion analysis collect data through crawler technology. Such as massive data. One is to provide data obtained from SaaS services, such as Talkindata. The other is the data obtained by data mining in cooperation with operators or the government, such as AsiaInfo and Jiufen. The last one is the data generated by its own platforms (e-commerce, tourism, media and other Internet companies), including BAT and some larger Internet companies such as 360, Dangdang, Vipshop, Jumeiyou, Ctrip, and Today's Headlines.

First, the value of open data.

Open data is desensitized data released by the government to the society. Including weather data, GPS data, financial data, education data, traffic data, energy data, medical data, government investment data, agricultural data and so on. These raw data itself has no obvious commercial value, but after processing by some companies, it can produce great commercial value.

Open data has a market of hundreds of billions of dollars in the United States, including 30 billion dollars of meteorological data, 90 billion dollars of GPS data and hundreds of billions of dollars of medical data. However, the data opened by the government is raw data, and the commercial value of the data itself is not great. It requires professional companies to collect, clean, mine and display data, thus forming data with commercial value. There are many companies in the United States that realize their commercial value by processing public government data, such as Zillow, the weather channel and Garmin, which process weather data, and their total market value has exceeded10 billion US dollars.

1, the main scope of government open data

A scientific data collected and manufactured by the government. For example, weather data, government-funded medical research data. These data can be used as public resources.

B government operation data, such as government expenditure or large-scale project operation data. On the one hand, open data can increase people's trust in the government, on the other hand, it can also bring business opportunities to some companies.

C regulatory industry data. These data are provided by enterprises to the government for processing. These macro data have great influence on the industrial planning and investment strategy of enterprises.

2. The challenge of China's open data road.

The data governance of a country has not been completed. A lot of data is either centrally managed or in an information island state. These are all problems that need to be solved in open data. The huge investment and long cycle of data governance are huge challenges.

B some public data are not in electronic form yet. For example, medical data and educational data are still in the state of paper records in some areas, and no electronic files have been formed. The electronization of these data is also a big challenge.

C desensitization and integration of open data will be a major challenge. In particular, the data of state-owned enterprises, which data can be made public, which data need desensitization, and how to integrate data from various places are all challenges.

D big data service companies and big data talents are scarce. As the big data market has just started, and there is a lack of big data talents and big data service companies in the market, public data may be difficult to generate commercial value in a short time, which will affect the enthusiasm of the government and enterprises to open data, which is not conducive to the formation of a benign big data commercial market, and will affect the sustainable development of open data projects.

3. Some suggestions on opening data.

Human society is about to enter the digital age, and open data will be a huge productivity. The government has recognized the value of open data and will continue to promote the data opening of the government and state-owned enterprises. Even if the investment in open data has no commercial value in a short time, its future economic value will prompt the government to adhere to the policy of open data and continue to invest. Just like the highway in China, open data is another information highway, which turns data into assets and huge social productivity, and helps enterprises realize greater commercial value.

For the government of data owners, it is necessary to complete data governance and data integration under the premise of ensuring public safety and personal privacy, gradually open data to the society, improve data quality, make public access to all individuals and enterprises, effectively use government science and technology funds, let interested enterprises and individuals participate in open data projects, encourage innovation, accept external challenges, and use collective wisdom to achieve optimal data selection.

For state-owned enterprises, it is necessary to open data on the premise of protecting their own commercial interests and help the development of their respective industrial chain enterprises. At the same time, open data can also help them to make industrial planning, make effective investment, find market opportunities and risks, operate steadily and make scientific decisions. Enterprises can use open data to improve production efficiency, reduce waste of resources and reduce the risk of decision-making mistakes. The benign development of industrial chain enterprises will also promote the development and evolution of state-owned enterprises, improve their competitiveness, optimize their operations and achieve industrial success.

For entrepreneurs, open data will be a new resource to help enterprises develop and focus on new business opportunities, especially in the health care industry, financial industry, energy industry and education industry. Data service companies can use open data to help consumers tap the potential value of data and provide valuable business data for enterprises and governments. For operating companies, we can use open data to evaluate business partners and potential investments, build consumer loyalty by providing data, learn to operate in a transparent business society, look for opportunities for public or private cooperation, focus on our own products and customers, and provide better products and services for consumers.

Second, the trillion-dollar big data market

In 20 14, the proportion of consumption in GDP has exceeded 50%, which indicates that China's economy is transforming into a market economy. Consumption accounts for 50%-70% of GDP, which shows the transition from moderately developed countries to market economy. The biggest engine of China's economic growth in the future should come from consumption, especially personal consumption. China is experiencing economic restructuring and urbanization, with huge personal consumption demand, rich social products, smooth channels, reduced logistics costs and improved transportation capacity. However, the total retail sales of social consumption is not growing fast enough, the allocation of resources is unbalanced, and the overall consumption level of society is still at a low level. These problems are becoming a difficult problem in China's economic development, and both enterprises and society need to solve them.

The commercial application of big data will help enterprises solve these problems; The effective use of big data will improve the level of social consumption, help enterprises improve efficiency, gain insight into customers and increase income. The commercial application of big data will be a trillion-dollar market in the future, and big data is a big business.

The most important feature of the era of big data is that all human behaviors are recorded by data, whether it is in the purchase behavior of e-commerce, or in travel and vacation, entertainment activities, behavior trajectories, etc. All human social behaviors are recorded by various sensors and the Internet. Data records everything, and the behavior of human society has also become data. The era of recording human history with paper media has passed, and history is being recorded by words, data, tables, sounds, images and other forms of data. The application of big data in China mainly focuses on credit reporting and precision marketing. The combined scale of these two markets is only 200 billion, but if big data is combined with the business needs of all enterprises, its chemical reaction will be huge, and the market scale will exceed one trillion. Big data is a big business.

Baidu connects information with readers, Ali connects goods with consumers, and Tencent connects people. All connections of BAT are based on data, and it can be considered that big data connects everything. Data connection consumers and merchants, data connection customer habits, data connection customer preferences, data connection location, data connection time and space, data connection history and present. Big data connecting everything will feed back the connected things, space and time, and feed back the movement of objects, customers' consumption habits, personal hobbies, behavior habits, activity trajectories, movement rules and so on through data records. You can know important feedback data; Who you are, where you are, what you like, what you are doing, your spending power, and your future needs. All the contents of the feedback have one or more data labels. After sorting out and analyzing these valuable labels, it will reveal the correlation and law between things and bring great value to individuals, enterprises and society.

1. Big data helps the manufacturing industry plan production and reduce waste of resources.

In the past, the manufacturing industry faced the pressure of overproduction. Many products, including home appliances, textile products, steel, cement and electrolytic aluminum, are not produced according to the actual needs of the market, resulting in a great waste of resources. Use e-commerce data, mobile internet data and retail data to understand the future market demand of products and customize products for customers.

For example, based on the product data and logistics data searched by users in e-commerce, we can infer the actual demand of home appliances and textile products in the future, and manufacturers will produce according to these data to avoid overproduction. The location information of mobile internet can help to understand the trend of local population in and out and avoid producing too much steel and cement.

2. Mobile big data helps real estate developers plan real estate development.

The real estate industry contributed a lot to China's GDP in the past. In the future, the extensive real estate industry will turn to refined management. From site selection to planning, from design to construction, we need to make scientific decisions with reference to local population data and consumer information. Use big data business applications to speed up housing sales and reduce their own liabilities.

Real estate companies can use people's mobile phone positioning information to help enterprises carry out development planning, land location, shop development and so on. At the same time, using the portrait information of people to users, we can help real estate companies choose cooperative merchants, enhance consumer popularity and ultimately enhance the value of real estate.

3. Mobile big data helps the catering and retail industry to conduct site selection and customer diversion.

The catering and retail industry is most concerned about passenger flow. In the past, when opening a shop, people were often arranged to count the traffic at the crossroads, and the location of the shop was determined by using the statistical traffic information. After entering the era of mobile internet, the location information of smart phones can help the catering and retail industry to choose the location of stores, and enterprises can refer to customer portraits to determine the size of stores and product categories.

User tags and portrait data on the mobile internet can also help enterprises to carry out some precise marketing and introduce passengers to newly opened businesses. Especially in large shopping malls, the location navigation function of mobile App can guide customers to find new businesses and participate in promotional activities. There are mature retail catering businesses and mobile internet big data companies in the market to open stores for drainage. The leverage ratio of capital utilization is more than five times, and the input and output are relatively high.

4. The sensor data helps the product to carry out fault diagnosis and prediction.

Household appliances and cars are becoming intelligent. By installing sensors, cars and smart home appliances can transmit their operating parameters and operating status to the cloud platform of manufacturers, so that manufacturers can know the operating status of their products and the aging degree of parts, help manufacturers to replace faulty devices in time, prolong the service life of products and improve the safety factor. The automotive industry and smart home appliances will have a huge market in the field of Internet of Things, and cloud computing and big data processing platforms will play a key role.

China's automobile market has a sales scale of more than one trillion yuan, and the home appliance market also has more than one trillion yuan. The big data application market involved in the Internet of Vehicles and smart home appliances is also huge. According to the high leverage ratio of big data business, its market size should be at least around10 billion.

5. Use the location information of the mobile Internet for accurate marketing.

O2O has become an important business model. Many Internet companies and traditional enterprises are looking for O2O application scenarios. Ordering, education, housekeeping and car beauty have all become the application modes of O2O. Mobile Internet data has the characteristics of LBS and real-time, which can help enterprises to connect customers in time and conduct accurate marketing according to customer needs.

Large shopping centers generally have cinemas, and it often happens that some movies have not sold a large number of movie tickets 30 minutes before the opening. With the push advertising function of the mobile App, the cinema can push the movie tickets to customers who are eating around at a price of 20% 30 minutes before the movie is shown. According to the customer portrait information, the movie ticket is pushed to the customers who like watching movies, so as to increase the movie sales. Enterprises can use mobile App to push advertisements, so that thousands of people can push advertisements according to customers' preferences. This kind of accurate advertising push has the characteristics of low cost and high conversion rate, and has achieved good application results in catering, clothing, beauty, retail and other industries. If accurate advertising push based on location information is applied to large-scale businesses, it will promote the circulation of commodities, greatly increase the total social consumption and help traditional enterprises realize the internet plus strategy.

6. E-commerce big data will help enterprises optimize resource allocation.

E-commerce is the first industry to use big data for precision marketing. The recommendation engine in e-commerce website will recommend related products according to customers' buying behavior. In addition to precision marketing, e-commerce can also prepare goods for customers in advance according to their consumption habits, and take convenience stores as transit points to deliver goods to customers within a short time after placing orders, thus enhancing the customer experience. E-commerce can also use its transaction data and cash flow data to provide small loans to businesses in its ecosystem, and can also provide these data to banks to support SME credit.

The data of e-commerce is large enough, concentrated and varied, and its commercial application has great imagination. Including forecasting fashion trends, consumption trends, regional consumption characteristics, customer consumption habits, consumption behavior correlation, consumption hotspots and so on. Relying on big data analysis, e-commerce can help enterprises with product design, inventory management, planned production and resource allocation. , which is conducive to refined mass production, improving production efficiency and optimizing resource allocation.

7. Mobile big data helps traffic planning and management.

The application of traffic big data is mainly in two aspects. On the one hand, we can use the data of big data sensors to understand the traffic density of vehicles and make reasonable road planning. On the other hand, big data analysis can be used to realize intelligent switching of traffic lights and improve the transportation capacity of existing lines.

In the United States, the government added traffic lights according to the traffic accident information of a certain section, which reduced the traffic accident rate by more than 50%. Big data can help airports arrange flight take-off and landing and improve management efficiency; Airlines can use big data to increase attendance and reduce operating costs; Railway companies can use big data to arrange passenger and freight trains and reduce operating costs.

8. Big data helps the financial industry realize value.

Big data is widely used in the financial industry. A typical case is that Citibank uses IBM Watson computer to recommend products for wealth management customers, and Bank of America uses customer click data sets to provide customers with special services. China Merchants Bank (600036, Share Bar) uses the behavioral data of customers' credit card swiping, deposit and withdrawal, electronic bank transfer, WeChat comments and so on for analysis, and sends targeted advertising information to customers every week.

At present, the value changes of big data in China's financial industry are mainly in two aspects: user experience improvement and big data marketing. Among them, China Merchants Bank Credit Card Center and Ping An Bank (00000 1, stock bar) have already reached the front of the financial industry.

Big data has a wide range of application scenarios in many industries, such as medical industry, agriculture, forestry, animal husbandry and fishery, energy industry, logistics industry and so on. Big data will be another huge market after relay operators. After integrating the business needs of all industries, the market size of the big data industry will be trillions. Big data is not electricity, but it can provide more power than electricity. Big data is not oil, but it can drive the development of enterprises more than oil. Big data is an asset that can help enterprises realize value. The business of big data is actually very simple, that is, income increases and expenses decrease; It is to increase customers, improve customer experience and increase the leverage ratio of capital return; After the application of big data matures, big data can predict the business future and discover new business opportunities.