How to deal with the growth of big data "trouble"
Today, almost no one will doubt the value of big data, people are more concerned about how to really push the big data to the application of the real value. However, despite the industry's exploration, the overall development of Big Data is still in its infancy. In other words, the recognition of the concept of big data does not mean that it can be utilized. Especially in China, although big data has a good industrial foundation and development prospects, the low degree of openness of data resources, the protection of data assets and other practical issues are the main challenges currently facing. How to cope with these challenges and drive big data toward universal application rapidly? Recently, the Telecommunications Research Institute of the Ministry of Industry and Information Technology released the "Big Data White Paper", which gives a unique answer to the above questions.
Effective application model has not been found
Currently, big data has not yet formed the situation of universal application. The reason for this is that most enterprises, especially those in traditional fields, have not yet found an effective application model.
The application of ideas is faster than the application of data
Data is an asset. This wave of big data has led to the rapid popularization of the big data concept. Although much of the data has yet to find a suitable use, many companies are already treating it as an asset, planning and storing their data, or developing it on their own, or actively searching for buyers, or looking for collaborators.
Telecom operators are most likely to be the typical data asset operators. Telecom carriers hold rich user identity data, voice data, video data, traffic data and location data, and the massive, diversified and real-time nature of the data gives them an inherent advantage in operating big data. At present, major telecom operators have been actively exploring the development of their internal big data resources, but from the current application development, telecom operators' big data is still mainly used to support internal customer churn analysis, marketing analysis and network optimization analysis, etc., and the external application model has not yet taken shape.
Big data applications are emanating
Currently, big data applications have not formed a prairie fire and are mainly focused on Internet marketing scenarios. Although the financial, telecom, retail, manufacturing, medical, transportation, logistics, IT and other industries have shown great enthusiasm for big data applications, the big data application cases made public in the media and various forums are still very scattered, which indicates that although everyone is concerned about big data, there are still some difficulties in advancing the actual application. The only area in which many companies are launching or adopting big data applications is Internet-based marketing, and the companies that have applied big data in this area include not only large Internet companies, many specialized small and medium-sized Internet companies, but also offline companies that are cooperating with Internet companies to actively develop the value of this area.
From the data source, the application of big data is still in the era of self-sufficient "small farm economy", and the existing application is still dominated by the internal data of the organization. The main reason for the predominance of intra-organizational data is that data opening and trading has not yet formed the mainstream form of the market. Take the major domestic e-commerce trading platform as an example, although many big data applications have been launched, these applications are basically limited to internal. Due to the unsoundness of laws and data trading mechanisms, these trading platforms are still cautious about opening and trading data to the outside world. a survey by Gartner shows that even globally, internal data domination is still the main feature of big data applications, and the most applied in various industries is still the internal transaction data (the application ratio is generally more than 50%, with the ratio of application in most industries exceeding 80%) and log data.
From a technical point of view, big data is still mainly used in primary applications, and most applications still use traditional analyzing processes and tools, only expanding the sources and increasing the quantity of data. The research found that compared with traditional data analysis, although new big data applications are starting to use unstructured data, in the actual application process, these unstructured data are just compressed, cleaned and structured and put into the traditional ETL and analysis processes. Some other big data applications have improved data processing efficiency by adopting cloud storage and cloud processing technologies, thus increasing the scale of data processing, but these applications also still use the original ETL and analysis processes. The lack of innovation in the application model makes the current big data applications still in the primary technology stage.
From the point of view of the application effect, the current big data applications to continue to improve the existing business and product-oriented, breakthrough innovative applications are not yet common. To the most common Internet marketing big data applications, for example, before the rise of big data, precision marketing and personalized recommendations has been the direction of the pursuit of business marketing activities, emerging data sources and the rise of big data technology makes the enterprise to further improve its marketing skills, so that its precision marketing capabilities to further enhance the ability to do so, but this is only the improvement of the enterprise's old marketing capabilities. The breakthrough innovations that are currently being discussed are the online microfinance business, which has completely changed the process of lending, credit evaluation and risk control of financial institutions in the past, thus greatly reducing the cost of lending and expanding the scope of lending. However, such breakthrough innovations are not common at present, and Gartner's survey shows that the main purpose of enterprises investing in big data is to improve customer service, process optimization, precision marketing, and cost cutting, etc., and the direction of breakthrough innovations such as new products/new business models is not the main purpose of enterprises.
Different Chinese troubles
Currently, the development of big data in the world is still in the early stage, and technology, systems and concepts need to be changed. Specifically for China, the lack of abundant data resources, large technology gaps and imperfect laws and regulations are the unique problems facing the current development of big data.
Insufficiently abundant data sources and low degree of data openness
An abundance of high-quality data resources is a prerequisite for the development of the big data industry. In recent years, driven by the rapid development of the Internet industry and financial and telecommunication informatization, the total amount of data resources in China has seen rapid growth, reaching 13% of the world's total, but other industries are constrained by the level of informatization, and data reserves are still not abundant. Existing data resources also have low levels of standardization, accuracy and completeness, and low utilization value. At the same time, China's government, enterprises and industries are constrained by various factors in the construction of informatization systems, forming many "information islands", and the degree of data openness is seriously lagging behind. The establishment of a benign development of data resources reserves and **** enjoyment system, is the primary issue of China's big data development.
Technology level is not high, technology diffusion is not smooth
China's big data technology development model is also similar to the global, Internet companies have the ability to quickly integrate international advanced open source big data technology into their own systems, and build a single cluster of tens of thousands of nodes in the large-scale system, but there is still a lack of original technology, the lack of contribution to the open source community, and then the impact of the cutting edge of the technology line is relatively weak. At the same time, due to the lagging development of local open source communities and other industrial organizations, it is also difficult for the technological innovations of leading domestic enterprises in big data to spread to society.
Related laws and regulations need to be further improved
With big data mining and analysis becoming more and more accurate and application fields expanding, the protection of personal privacy and data security have become very urgent. In terms of privacy protection, the existing legal system faces two challenges: First, the legal protection of personal privacy should be reflected as "personally identifiable information (PII)", but with the advancement of technology, data that was not PII in the past may also become PII, making the scope of protection vague. Secondly, the previous personal information protection system based on the principles of "clear purpose, prior consent, and restriction of use" has become increasingly difficult to operate in the big data scenario. The laws and regulations on personal information protection and cross-border flow of data in China are not yet sound, which has become one of the major reasons restricting the healthy development of the big data industry. It is necessary to combine the actual situation of the construction of the rule of law in China and explore ways to make up for the shortcomings of the imperfect legal system through industry self-regulation and other means.
Multiple measures out of the development of misunderstanding
For the development of China's big data industry, first of all, we need to clarify the strategic objectives and strategic focus, integrated planning of big data applications, key technology research and development and industry cultivation, data openness and data protection, market supervision, laws and regulations, and other key layout, to guide the direction of the development of big data around the country, to avoid blind development of a flurry.
In terms of big data application, one is the application in the field of government affairs and public **** services, which should focus on improving people's livelihood services and urban governance, etc., and actively promote the integration of environmental protection, medical care, education, transportation, and other key areas of big data consolidation and integration of applications to further improve the efficiency of government affairs and public **** services. The second is market-oriented application, should focus on cross-industry big data applications to introduce policies to promote the Internet, telecommunications, finance and other enterprises and other industries to carry out big data integration and application innovation, leading to the deepening of the whole society's big data applications.
In terms of technological innovation, the first is to strengthen the forward-looking and systematic direction of big data technology research and development, and in the near future, focus on supporting deep learning and artificial intelligence, real-time big data processing, massive data storage and management, interactive data visualization, and application-related analytical technologies. Secondly, we should gather the power of industry, academia, research and application to form a synergy, and strive to achieve breakthroughs in big data platform-level software, which is the core of the development of open source ecology. Third, innovative research project support methods, open source and open standards as assessment indicators, through direct subsidies or post-subsidies to incentivize enterprises and research institutions to participate in the development of open source technology to promote the proliferation of big data technology.
On the opening of government data, it is recommended to promote the census of data resources in the government and public utility fields, and to formulate a checklist for security and privacy protection in the opening of government and public ****data in accordance with the relevant regulations, so as to strictly control the points of risk that may involve national security and citizens' privacy. On this basis, government and public **** data should be categorized by sensitivity, openness priorities should be determined, and a step-by-step roadmap for data opening should be developed. At the same time, the government should also actively regulate and guide commercialized big data trading activities to create favorable conditions for the circulation of data resources.
In terms of personal information protection, some international organizations have proposed that the focus of regulation should be "shifted from data collection to data use". We need to pay close attention to the evolution of international legislative concepts, combined with technological development trends and China's national conditions to carry out forward-looking research on the relevant system. At the same time, in order to address the urgent need for personal information and data protection, we can rely on industry organizations to summarize the industry's best practices in a timely manner, and gradually form an industry **** knowledge, in the pilot after the maturity of the standards or laws and regulations and promote the implementation of the healthy development of big data escort.
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