IC694MDL753 Forced number of insufficient power enterprises to release data capabilities

However, at present, a large number of industrial enterprises in China still have insufficient power for digital transformation, and are still in the process of informatization, and they have not formed a data system or a complete data strategy to guide the generation of data assets.

IC694MDL753 In the view of Wu Dayou, the main person in charge of the International Data Advanced Management Research Institute, the data transformation of industrial enterprises can not just sell equipment and tools. Tools or equipment must have the ability to collect data legally, we need to think about remote data linkage, be able to monitor data, monitor the normal operation of the equipment, be able to predict the possible failure of the equipment in advance, and achieve “zero failure” service.

IC694MDL753 Now more and more enterprises realize that the digital cost reduction and efficiency increase of the industrial industry will inevitably come to a bottleneck period, because all the digital transformation if the goal of cost reduction and efficiency is to meet the “threshold”, the cost can not be zero, and the benefit will not be infinite. Enterprises want to change business mechanisms or service models, and in this process, data assets into the table is actually forcing enterprises to release data capabilities at the same time, but also forcing digital business models to change. Enterprise data assets will promote the upgrading of traditional business forms of enterprises, and the precipitation of data assets will ultimately create real value for users, so as to generate effective power points.

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IC694MDL753 Zhang Xu, chief data officer of UF Network’s large enterprise customer business group, also believes that if it is only to reduce costs and increase efficiency, “there will be a head”, but the company can provide better goods and products to the society, its future can be very much. He mentioned that UFyou’s “industrial big data +AI” solution is based on big data technology and a new generation of AI technology, integrated into the entire industrial life cycle business scenario, mining the value of industrial big data, helping manufacturing enterprises to achieve reasonable production scheduling, optimize ingredients, quality diagnosis, fault prediction, safety warning, and play with data assets to make production simpler and quality more stable. Lower cost, more scientific decision-making.

IC694MDL753 Wang Xiangwang believes that the data sources of industrial enterprises are complex and diverse, and the data scale is larger, which needs to be supported by a special data governance and data asset management platform for industrial enterprises, which is the technical guarantee for realizing data assets. In addition, in terms of operation and management, production and operation, industrial enterprises have many scenarios that can drive the transformation from data resources to data products and data services, such as strategic decision-making, production improvement, operation optimization, risk prevention and control, etc., which is an important engine to realize data capitalization, requiring specialized manufacturers to provide service support.

The open source design of industrial data resources is very valuable, and there will be new business conversion opportunities when large enterprises take the lead and open source the ecosystem. Yan Yang predicted that with the development of large models, meta-universes and the advancement of future enterprise data assets into the table, if enterprises can seize the opportunity to grow up, it may become a new “unicorn”.