"'Internet+' and 'Made in China 2025' are the two main driving forces for economic restructuring and development in China at present and in the near future. The main combination of the two is smart manufacturing, and industrial big data is the driving force for smart manufacturing. On March 14, Nguyen Nguyen, deputy to the National People's Congress and director of the Economic and Information Committee of Anhui Province, revealed to reporters that this time he submitted a proposal to the General Assembly concerning the development of cross-border integration of big data and manufacturing industries. China should realize cross-border manufacturing integration through the promotion of big data applications. Again, it is difficult to apply data integration in various departments of a company. The integrated application of internal data in enterprises is the first step in achieving production and business collaboration. However, the isolation of information between internal departments of many companies is relatively serious. The basic data is collected and collected by the system. Data between different departments has not yet been opened and integrated. , resulting in extremely low data utilization, adding a threshold for the application of industrial big data. NMN For Face Cream,Nicotinamide Mononucleotide For Face Cream,β-Nicotinamide Mononucleotide,CAS 1094-61-7 Changshu Enzyme Biotechnology Co., Ltd. , https://www.nmnglutathione.com
Nguyen believes that at present, there are mainly the following problems in the application of industrial big data in China: First, the technology system for excavating the value of industrial big data has not yet been established. At present, China is still in the exploration stage of promoting intelligent manufacturing. For most companies, self-sensing, self-memorizing data acquisition and sensing systems have not yet been established, data processing technologies that deal with complex data structures still need to be improved, and efficient database maintenance and management The mechanism needs to be improved.
Second, there is insufficient application of data integration within and outside the industry. At present, the overall application of China's big data is still in its infancy. Strip data collection and application are widely used. Block data applications are lacking. Intra-industry data and external data are not integrated enough. Cross-industry interaction aggregation has not yet emerged, as is industrial big data. .
Finally, industrial big data processing services are weak. Due to different customer needs, production environments, etc., different industries and different companies have different data collection, processing and mining directions. This requires industrial big data processing service companies to have both industrial industry expertise and big data processing capabilities. At present, China's data processing service companies have weak forward forecasting capabilities, and most of them only use data for backward disclosure and analysis of reasons.
To this end, Niu Yijianyi: First, strengthen the organizational leadership of industrial big data applications. Strengthen the top-level design, formulate the "Guidance Opinion on Promoting the Application of Industrial Big Data" as soon as possible, specify the technologies, standards, and industries for the application of industrial big data, formulate development paths, and plan and promote the establishment of a core intelligent technology system that taps into the value of industrial big data. The second is to increase financial and taxation finance, investment and financing policy support efforts. Set up a national special fund for the development of industrial big data to play a role in amplifying the special funds, and guide social capital to actively participate in industrial big data applications through investment subsidies, fund injections, guarantee subsidies, and loan discounts. The third is to improve the promotion and application mechanism. Implement a batch of pilot projects with distinctive big data applications to explore new models and new formats for the big data industry. Regular exhibitions of outstanding achievements in the application of industrial big data are held to expand the social impact of industrial big data applications. The fourth is to build effective talents to foster the introduction and incentive mechanism. Actively create an external environment that is conducive to the training and development of industrial big data talents, and build multi-level industrial big data talent structures that are leaders, scientific research, complex, and practical. Pay attention to employment and entrepreneurship guidance for big data talents, formulate more open and effective incentive policies for talents, and establish applicable talent reward funds to stimulate entrepreneurship, innovation and creativity. Accelerate the process of the professionalization of big data talents, establish vocational qualification examinations and certification systems such as big data analysts, and lead the implementation of the chief data officer (CDO) system in state-owned large and medium-sized industrial enterprises.