The business of big data is actually very simple, is to increase revenue, spend less; is to increase the number of customers, improve the customer experience, improve the leverage of the return on capital; after the maturity of the application of big data, big data can predict the future of business, to find new business opportunities.

A stone stirred up a thousand waves, the State Council issued the 2015 No. 50 "to promote the development of big data action program" brushed full of friends, in particular, which mentioned vigorously promote the government sector data *** enjoy, steadily promote the opening of the public *** data resources. 2017 by the end of the formation of cross-sectoral data resources *** enjoy the pattern, by 2018 to achieve the full coverage of the unified *** enjoy the platform and data *** enjoyment and exchange. 2020 to cultivate 10 leading international big data core leading enterprises, 500 big data applications, services and product manufacturing enterprises.

It is well known that the commercial value of big data is huge. But the commercial value of big data in China has not been fully tapped. The main difficulty lies in the dispersion of big data, with most of the valuable data concentrated within the government, monopoly state enterprises, and Internet giants. The dispersed data cannot help enterprises get valuable information and realize the commercial realization of big data. The government's opening up of data and the establishment of a big data trading market is the most important task for the application of big data business value in China.

Additionally, the application scenarios of big data and big data privacy issues are also two major problems in the commercial application of big data. Without knowing the application scenarios of the data, there is no way to find the data with value, there is no way to make the data work, and the application of big data will stay at a low level of solving the 1.0 era of big data such as data collection, processing, storage, and so on, and will not be able to realize the commercial realizations of the big data, and cannot motivate the enterprises to further invest in big data, and cannot form the basis for the development of big data. Enterprises will not be able to further invest in big data, and the ecological cycle of data value application will not be formed. Big data privacy is a problem that all enterprises can not avoid. What kind of data can be exchanged, what kind of data can be collected and realized, and what kind of data can be circulated in the market as commodities, these issues affect both the protection of personal privacy and the enthusiasm of enterprises to buy data products, as well as the development of data enterprises.

China's big data companies are divided into three categories. One category is big data technology companies, which provide enterprises with big data platform construction, technical consulting, and big data computing and storage products, such as Huawei, AsiaInfo, Wave and other traditional IT companies. One category is big data service companies, providing enterprises with services, platforms and products based on big data technology. Including for enterprises to build big data mining tools, search engines, analytical engines and other big data processing platforms, big data cleaning and mining services such as Mingliu Technology, ADMaster, percent. The last category is to provide data products of big data companies, they have data, processing to generate valuable data, to provide standard data products for the market. Examples include Sesame Credit, TalkingData, Nine Times Square, and StarMap Data.

There are four types of data sources in China's big data market, one is external data collected through web crawlers, and most of the companies that provide public opinion analytics do so through crawler technology. For example, massive data. One is the data obtained by providing SaaS services, such as Talkindata. another is the data obtained through data mining by cooperating with operators or the government, such as AsiaInfo and Nine Times Square. The last is the data generated by its own platform (e-commerce, tourism, media and other Internet companies), including BAT and some larger Internet companies such as 360, Dangdang, Vipshop, Jumiaoyou, Ctrip, and Today's headlines.

I, the value of open data

Open data is the government to the community to publish their own owned, and after desensitization of the data. It includes weather data, GPS data, financial data, education data, transportation data, energy data, medical data, government investment data, agricultural data and so on. The raw data itself has no obvious commercial value, but after being processed by some companies, it can generate huge commercial value.

Open data has a market of hundreds of billions of dollars in the United States, including $30 billion in weather data, $90 billion in GPS data, and hundreds of billions of dollars in medical data. But the government's open data is raw data, the commercial value of the data itself is not large, the need for professional companies to collect data into the collection, cleaning, mining, show, so as to form a commercial value of the data. In the United States there are many companies rely on the processing of government open data to achieve its commercial value, such as processing weather data Zillow company, the weather channel company, as well as the processing of GPS data Garmin company, their total market value has exceeded ten billion dollars.

1, the main scope of government open data

a scientific data collected and manufactured by the government. Examples include weather data, government-funded medical research data. These data can be used as public **** resources.

b Data on government operations, such as government spending or data on the operation of large-scale programs. Open data can increase people's trust in the government on the one hand, and can open up business opportunities for some companies on the other.

c Data from regulated industries. These data are provided to the government by companies and are processed by the government twice. These macro data have a great impact on industry planning, and investment strategies of companies.

2. Challenges on the road to open data in China

a National governance of data is not yet complete. A lot of data is not centrally managed and is still in the state of information silos, which are problems that need to be solved for open data. The huge investment in data governance and the long time cycle are all huge challenges.

b Some open data is not yet in electronic form. Medical data and education data, for example, are still in paper records in some areas and are not in electronic form. Electronicization of these data is also a bigger challenge.

c Desensitization and integration of open data will be a major challenge. Especially for state-owned enterprises, which data can be made public, which data needs to be desensitized, and how to integrate data from various places will be a challenge

d There is a lack of big data service companies and big data talents. As the big data market has just started, there is a lack of big data talents and big data service companies in the market, and it may be difficult to generate commercial value for a short time for the open data, which will affect the enthusiasm of the government and enterprises to open up the data, and will not be conducive to the formation of a benign commercial market for big data, which will affect the sustainable development of the open data project.

3. Some suggestions about open 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 open data in government and state-owned enterprises. Even if the investment in open data does not see commercial value in a short period of time, its future economic value will motivate the government to stick to the policy of open data and continue to invest. Like China's highways, open data is another information superhighway that transforms data into an asset, into a huge social productivity, and helps companies realize greater business value.

For the government, the owner of the data, it needs to complete data governance and data integration under the premise of safeguarding public **** security and personal privacy, gradually open data to the community and improve data quality, openly face all individuals and enterprises, effectively utilize government science and technology funds, allow stakeholder enterprises and individuals to participate in open data projects, encourage innovation, accept external challenges, and utilize collective wisdom to realize the optimal choice of data.

For state-owned enterprises, they need to open up their data under the premise of protecting their own commercial interests to help the development of their respective industrial chain enterprises. At the same time, open data can also help their own industrial planning, effective investment, discovering market opportunities and risks, sound operation and scientific decision-making. Enterprises can utilize open data to improve productivity, reduce waste of resources, and lower the risk of decision-making errors. The benign development of industrial chain enterprises will also promote the development and evolution of SOEs themselves, improve competitiveness, optimize business operations, and achieve industrial ****win.

For entrepreneurs, open data will be used as a new resource to help companies develop and focus on new business opportunities, especially in the health care industry, financial industry, energy industry, and education industry, where open data has a greater impact. Data service companies can utilize open data to help consumers tap into the potential value of their data and provide valuable commercial data to businesses and governments. For companies in business, they can use open data to evaluate business partners and potential investments, build consumer loyalty by providing data, learn to operate in a transparent business community, look for opportunities for public*** or private partnerships, focus on their own products and customers, and provide better products and services to consumers.

The second trillion dollar big data market

The proportion of consumption in the GDP in 2014 has exceeded 50%, marking the transition of China's economy to a market economy, consumption accounts for 50%-70% of the GDP is a manifestation of the transition of the middle developed countries to a market economy, and the future of China's economic growth, the largest engine should be derived from the consumption, especially personal consumption. The biggest engine of China's future economic growth should come from consumption, especially personal consumption. China is undergoing economic restructuring and urbanization, and there is a huge demand for personal consumption. Social products are more abundant and the channels are smoother, logistics costs are decreasing, and transportation capacity is improving. However, the total retail sales of social consumption is not increasing fast enough, the allocation of resources is unbalanced, and the overall consumption level of society is still at a relatively low level. These issues are becoming difficult problems for China's economic development and are problems that need to be solved by enterprises and society.

The commercial application of big data will help enterprises to solve these problems; the effective utilization of big data will increase the level of social consumption, and will help enterprises to improve efficiency, customer insight, and increase revenue. The commercial application of big data is a trillion-dollar market in the future, and big data is big business.

The most important feature of the big data era is that all human behavior is recorded by the data, whether it is in the purchase of e-commerce, travel and vacation, entertainment activities, behavioral trajectory, etc., all of the human social behaviors are recorded by a variety of sensors and the Internet. Data records everything, the behavior of human society has become data, the era of using paper media to record human history has passed, history is being recorded by data in the form of text, data, forms, sound, image. China's big data applications are mainly focused on credit and precision marketing, the size of these two markets together is only two hundred billion, but if big data is combined with the business needs of all enterprises, the chemical reaction will be huge, the market size will be more than a trillion, big data is a big business.

Baidu connects information and readers, Ali connects goods and consumers, and Tencent connects people to people. all of BAT's connections are built on data, and it can be argued that big data connects everything. Data connects consumers and businesses, data connects customer habits, data connects customer preferences, data connects location, data connects time and space, data connects history and the present. The big data that connects everything will feedback the connected things, space and time, the movement of objects, customer's consumption habits, personal preferences, behavioral habits, activity trajectories, movement patterns and so on through data records. Importantly this feedback data can tell; who you are, where you are, what you like, what you are doing, your spending power, and your future needs. All the things being fed back are tagged with one or more data labels, and these valuable labels, after being organized and analyzed, will reveal the correlation and laws between things, and will bring great value to individuals, businesses, and society.

1, big data to help the manufacturing industry to plan production, reduce the waste of resources

Manufacturing industry in the past faced with the pressure of overproduction, many products, including home appliances, textile products, steel, cement, electrolytic aluminum and so on are not in accordance with the market's actual needs of production, resulting in a great waste of resources. Using e-commerce data, mobile internet data, and retail data, we can understand the future needs of the product market and customize products for our customers.

For example, based on the data of users searching for products in e-commerce and logistics data, the actual future demand for home appliances and textile products can be inferred, and manufacturers will base their production on these data to avoid overproduction. Mobile Internet location information can help understand the local population in and out of the trend, to avoid the production of excessive steel and cement,

2, mobile big data to help real estate developers plan real estate development

Real estate industry in the past for China's GDP contributed a lot of power, the future of the rough real estate industry will shift to the refinement of the operation, from the selection of land to the planning and design to the construction, all need to refer to the local population to the population, and to the construction of the real estate industry, the real estate industry is the most important factor. From land selection to planning and from design to construction, the industry will need to refer to local demographic data and consumer information to make scientific decisions, and utilize big data business applications to accelerate the speed of house sales and reduce its own debt.

Real estate companies can make use of the crowd's cell phone location information to help them carry out development planning, land site selection, store development, etc. At the same time, they can make use of the crowd's user profile information to help them make decisions. At the same time, the use of crowd to user profile information to help real estate companies to select cooperative merchants, enhance consumer popularity, and ultimately increase the value of the property.

3, mobile big data to help catering and retail industry for site selection and customer flow

The catering and retail industry is most concerned about customer flow, the past store site selection often arranged for personnel at the intersection of the flow of statistics, the use of statistical information on the flow of people to decide to open the store address. After entering the mobile Internet era, smartphone location information can help the restaurant retail industry to select the location of the store, the enterprise can refer to the customer profile to determine the size of the store, as well as the product category.

User labeling and profiling data on the mobile Internet side can also help companies conduct some precision marketing and introduce customer traffic to newly opened stores. Especially in large-scale shopping malls, the location navigation function of the mobile app can guide customers to find new merchants and participate in promotional activities. There are already established retail and catering merchants in the market and mobile Internet big data companies cooperating in opening stores to attract traffic, the leverage of capital utilization is more than 5 times, and the input and output are relatively high.

4, sensor data to help product troubleshooting and prediction

Home appliances and cars are moving towards intelligence, through the installation of sensors, automobiles and smart home appliances can be transmitted to the manufacturer's cloud platform of the operating parameters and operating status, manufacturers can understand the operating status of their products, the degree of deterioration of parts to help manufacturers to replace faulty devices in a timely manner, to prolong the service life of the product, to Improve the safety factor. The automotive industry and smart home appliances will generate a huge market in the field of Internet of Things (IoT), and cloud computing and big data processing platforms will play a key role.

China's automotive market has a sales volume of more than one trillion dollars, and the home appliance market has more than one trillion dollars. The big data application market involved in car networking and smart home appliances is also huge, and its market size should be at least around 10 billion according to the high leverage rate of big data commercial realization.

5, the use of mobile Internet location information for precision marketing

O2O has become an important business model, many Internet companies and traditional enterprises are looking for O2O application scenarios, ordering food, education, housekeeping, automobile beauty and so on have become a model of O2O application. Mobile Internet data with LBS and real-time characteristics can help companies connect with customers in a timely manner, based on customer demand for accurate marketing.

Large shopping centers are usually equipped with movie theaters, and there are often cases where a large number of movie tickets are not yet sold 30 minutes before the opening of certain movies. With the help of mobile app push ads, movie theaters can push movie tickets to customers who are dining around at a 20% discount 30 minutes before the movie. Based on customer profile information, movie tickets will be pushed to customers who love to watch movies, increasing movie sales. Enterprises can use mobile apps to push advertisements to thousands of people, based on customer preferences. This kind of precise 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 the precise advertisement push based on location information is applied in large-scale commercial application, it will promote the flow of commodities, greatly increase the total social consumption, and help traditional enterprises realize the strategy of Internet +.

6, e-commerce big data will help enterprises optimize resource allocation

E-commerce is the earliest use of big data for precision marketing industry, e-commerce website recommendation engine will be based on the customer's purchasing behavior, the associated product recommendations. In addition to precision marketing, e-commerce can also be based on customer consumption habits to prepare for customers in advance, and the use of convenience stores as a transit point for goods, in a short period of time after the customer orders, the goods will be delivered to the door to improve the customer experience. E-commerce companies can also use their transaction data and cash flow data to provide microfinance to merchants in their ecosystems, and they can also provide this data to banks to support credit for small and medium-sized enterprises.

The volume of data from e-commerce is large enough, the data is more centralized, and there are more types of data, so its commercial applications have more room for imagination. Including the prediction of popular trends, consumption trends, regional consumption characteristics, customer consumption habits, the relevance of consumption behavior, consumption hot spots and so on. Relying on big data analysis, e-commerce can help enterprises with product design, inventory management, planning production, resource allocation, etc., which is conducive to fine-tuning large-scale production, improving production efficiency and optimizing resource allocation.

7, mobile big data to help transportation planning and management

Transportation big data applications are mainly in two aspects, on the one hand, you can use big data sensor data to understand the density of vehicular traffic, reasonable road planning. On the other hand, big data analysis can be used to achieve intelligent switching of traffic signals to improve the transportation capacity of existing lines.

In the U.S., the government has reduced traffic accidents by more than 50% by adding signals based on information about traffic accidents along a certain route. Big data can help airports arrange flight takeoffs and landings and improve management efficiency; airlines can use big data to increase attendance and reduce operating costs; and railroad companies can use big data to arrange passenger and freight trains and reduce operating costs.

8, big data to help the financial industry for value realization

Big data in the financial industry has a wide range of applications, the typical case of Citibank to use the IBM Watson computers to recommend products for wealth management customers, the Bank of America to use the customer clicks on the dataset for the customer to provide special services. China Merchants Bank (600036, stock bar) using customer card, deposit and withdrawal, electronic banking transfers, WeChat comments and other behavioral data for analysis, weekly to send targeted advertising information to customers.

China's current financial industry big data value change mainly in the user experience to improve and big data marketing two aspects, of which China Merchants Bank credit card center and Ping An Bank (000001, stock bar) to the front of the financial industry.

Big data in many industries have a wide range of application scenarios, such as in the medical industry, agriculture, forestry, animal husbandry and fisheries, energy industry, logistics industry, etc., big data will be another huge market after the e-commerce, combined with all the industry's business needs, the market size of the big data industry will be a trillion-dollar level. Big data is not electricity, but more than electricity can provide power, big data is not oil, but more than oil can drive the development of enterprises. Big data is an asset that can help companies realize value. The business of big data is actually very simple, is to increase revenue, spend less; is to increase customers, improve the customer experience, improve the return on capital leverage; after the maturity of the application of big data, big data can predict the future of business, to find new business opportunities.