The data quality will vary significantly if the enterprise data governance system is not intact. It will affect data analysis, data application, data mining, etc., resulting in a lower overall value density of data.
Enterprises access a large amount of data, and after standardized governance, downstream business systems require data service input to improve efficiency. The previous data service development model cannot meet the requirements of rapid response and standardization.
There are a lot of architecture silos in the process of business system construction. Repeated construction of application systems results in a high degree of coupling between data and applications, and it is difficult to combine and expand horizontally, which cannot meet the requirements of rapid capacity opening as well as data and service sharing.
In an enterprise-level, data comes from multiple levels of business systems, and the phenomenon of data silos is widespread. The data types are diverse, and the data structures are varied. The data standards are strongly associated with their respective business attributes. Implementing top-level data standards is difficult, and data integration is challenging.
Based on a deep understanding of the data characteristics of the public traffic domain, the eSurfing Cloud data platform integrates the capabilities such as data collection and aggregation, data governance, data processing, and data services to accomplish asset management and service sharing of public traffic business data.
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Based on the “1231” architecture, a new smart city is built, which demonstrates digital, integrated, collaborative, and intelligent technologies as well as local characteristics. The urban data platform helps to accomplish the aggregation, integration, and sharing of urban multi-source heterogeneous data, which provides data support for upper-level business applications.
Cloud capacity deployment and smooth expansion X86 cluster, cloudification, containerization, and microservices deployment are supported to accomplish easy scalability, rapid deployment, and high availability. The Hadoop framework is used to achieve massive and unstructured data storage that cannot be supported by traditional architectures as well as the expansion and integration of AI algorithms, large videos, and other capabilities. Customization supported by open capabilities We provide a mature integrated development environment and data sandbox, establish a scientific data hierarchy planning, achieve separation of data processing and application, and enable efficient and secure capability opening of data, services, platforms, applications, etc., supporting the development and access of enterprise-level data applications and realizing personalized customization requirements. Extensively adapted to a large number of scenarios A wide variety of big data scenarios are supported including E-government, smart city, smart production, smart finance, public opinion detection, network security, network search, Internet of Things, and Internet of Vehicles to comprehensively facilitate the building of the platforms for the government and enterprises as well as the construction of applications.
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