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Unified aggregation promotes business data collaboration5
Value extraction supports precise service and scientific management6
Real-time perception assists efficient operation of urban governance7
Big data resource platform target system planning 11
Construction goals and ideas 12
Enable efficient collaboration, comprehensively optimize the data dynamic update and synchronization mechanism,
promote the complete collection of public data, synchronize and update public data in a timely manner as needed, form a big data hub, ensure
government affairs coordination between committees and offices
to drive data applications, and further improve the theme of the big data center Database construction
completed the theme database construction, promoted the integration of data resources and data analysis application
focused service empowerment, initially built a middle platform capability opening system,
built a unified stream data processing and business middle platform, and improved data sharing services, data analysis and visualization services, and improved Data sharing and open efficiency
Strengthen data operation, promote unified and standardized management and operation
and maintenance of the city's data, build unified data development and scheduling, enhance data management capabilities, establish unified data operation and maintenance and its own big data component technology stack, and ensure stable operation of the platform to ensure
security Controllable, improve data security and platform security management and control
Establish a complete platform security and data security management and control system to ensure data security management and control
Functional Framework of Big Data Resource Platform 13
2. Build the core capabilities of the data center and empower diversified application scenarios15
2.1. The overall implementation plan of the data layer - data architecture 16
◼ The big data resource platform supports the three core data services of data sharing and exchange (production function), data analysis, and data openness, including three data areas: big data resource area, open area and experimental area.
◼ Big data resource area: includes two major data resources, the municipal data lake and the municipal database
- Data lake: mainly stores the business database of municipal government departments, the unprocessed original business database, and supports storage of structured and unstructured various types of data, and for peer-to-peer sharing and exchanging data-
Municipal database: mainly used to store high-quality government data resources after a series of cleaning, conversion, loading, and governance steps, as well as sharing and exchanging government affairs of various departments and districts in the city data in process.
◼ Open area: It is mainly used to store data open to the outside world. It can provide a higher level of data security protection through the isolation of a separate external development area from the big data resource area.
◼ Experimental area: mainly used to store informal experimental data for technological innovation and technical verification.
2.2. The overall implementation scheme of the data layer - data layering 17
◼ The city-level database of the big data resource platform is divided into basic database, theme database, indicator database and special database for different data applications, industry fields and themes. The municipal database and data lake are divided into ODS, DWD, DWA and ST from the data level And so on four main levels.
◼ ODS layer data: The data at this layer is the posted source data of the data lake. Its data structure is consistent with the original data structure of the government application and other systems, and it is the data source of the municipal database.
◼ DWD layer data: This layer of data is the detailed data after cleaning the source data of the data lake. According to the data standard, clean and convert the pasting source data
to achieve data standardization and consistency.
◼ DWA layer data: shared model data that is horizontally associated and vertically aggregated according to the needs of upper-layer applications in the detailed data.
◼ ST layer data: application result data for different applications.
2.3. Realization scheme of big data resource area - municipal data lake 18
2.4. Realization plan of big data resource area - municipal database - public basic database 19
3. Create a full range of open service capabilities to enable smart cities to operate 20
3.3. Open service layer - AI middle platform service 22
• Infrastructure: Provide all infrastructure resources of the platform, including computing resources, storage resources, etc., to provide basic support for the entire platform;
• Platform components: including big data platform and container platform, providing the basic operating environment for the entire AI cloud platform;
• AI platform: It is the core business layer of AI platform, including data management service, model training service, model management service reasoning service, resource scheduling service and operation management service, providing end-to-end artificial intelligence R&D and production general capabilities for business users;
• A capability: includes various artificial intelligence A capabilities, such as image recognition ability, video analysis ability, natural language understanding ability, knowledge map, etc.;
• Business applications: including various artificial intelligence applications, such as crowd control, environmental governance, intelligent security, etc.
4.1.5. Data Management - Data Quality Management 29
6. Provide technical support for the security of relevant processes in each stage of the data life cycle34
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