Data service management method and system

Abstract

The invention discloses a data service management method. The method comprises the following steps: setting and publishing a data standard; checking the shared data model registered by the data provider, and establishing a standard data table; acquiring or original data uploaded by a data provider through the standard data table; performing quality management operation on the original data; constructing a central library data relationship table; performing data integration operation on the standard data according to the central library data relationship table, and storing the central library data table in a central library; establishing a resource sharing directory according to the central library data table and the sharing data model; and the auditing data demander sending data to the data demander passing the auditing through the permission application uploaded by the resource sharing directory. Correspondingly, the invention discloses a data service management system. By adopting the method and the system, the data standard can be maintained in time, the data integration degree and the data quality are improved, the workload of an administrator is reduced, the transmission efficiency of shared data is improved, and the data sharing experience is optimized.

Description

technical field [0001] The present invention relates to database technology, in particular to a data service management method and system Background technique [0002] At present, major universities have made great progress in information infrastructure, information systems, educational technology, and user services. The common practice is to collect business system data based on national standards to form a unified standard central library, and then use sharing tools to share data, which basically solves the process of data collection, processing, integration, and sharing. [0003] The comparative document CN 105512167 B discloses a multi-service user data management method based on a hybrid database, which is characterized in that it includes the following steps: S1: import user data into the system exit and entry module; S2: perform data processing on the user data Classification; S3: Screening and cleaning of classified user data; S4: Basic integration of user data afte...

AI Technical Summary

Problems solved by technology

[0005] 1. The data standards are recorded offline, and the data standards differ greatly, resulting in a large maintenance workload

[0006] 2. There are many and scattered data sources, and there is a lack of real and effective integration

[0007] 3. It is impossible to automatically identify data quality problems, and often wait until the user department encounters many problems when using the data before giving feedback

[0008] 4. The data requirements of the business system are collected by the administrator and then processed to complete the data exchange. Business personnel cannot participate, which increases the workload of the data administrator

[0009] 5. The data sharing platforms of different business departments are not unified, and the data sharing methods are relatively single

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