Data management system

Abstract

The invention discloses a data management system, comprising a system core part, a system data support database, a data input module, a data standard comparison screening unit, a metadata standardization comparison screening module, a model design standardization comparison screening module, a first data output module, a data distribution module, a data integration module, a data quality inspection module and a data quality analysis module, a data quality improvement module, a second data output module, a data numbering module, a data backup database, a main database, a data encryption module, a security key identification module, a data statistics tabulation module, an account login module, a display module and an operation module. The method has the beneficial effects that the accuracy and the safety of the data are greatly improved by standardizing and processing the data, an upstream system can be promoted to correct the data, and meanwhile, a clear data support can be provided for a decision-making layer.

Description

technical field [0001] This application relates to a data system, specifically a data governance system. Background technique [0002] Data is the result of facts or observations, a logical induction of objective things, and unprocessed raw materials used to represent objective things; data can be continuous values, such as sounds and images, called analog data; it can also be Discrete, such as symbols and text, are called digital data; data governance requires the use of a data governance system. [0003] Defects of existing data governance: first, the lack of a unified data source collection system; first, the lack of a standard data dictionary and metadata management dictionary; third, the lack of a relational model layer, no hierarchical division, and no subject division; fourth 1. Lack of blood relationship mapping system, unable to track tasks from superior to subordinate; 5. Lack of unified quality management system, unable to check data offset, value range, standard...

AI Technical Summary

Problems solved by technology

[0003] Defects of existing data governance: first, the lack of a unified data source collection system; first, the lack of a standard data dictionary and metadata management dictionary; third, the lack of a relational model layer, no hierarchical division, and no subject division; fourth 1. Lack of blood relationship mapping system, unable to track tasks from superior to subordinate; 5. Lack of unified quality management system, unable to check data offset, value range, standardization, etc.; 6. Lack of metadata management system, Unable to associate the business meaning of the data item with the data item

The disadvantage is that the first problem is that solution one is a technical solution used by many small and medium-sized companies. It supports most different types of data sources and supports real-time data collection and calculation. However, this solution does not support metadata management and cannot Carry out blood relationship mapping; the second problem is that the second solution is a simple and practical data integration tool that integrates data between different data sources through mapping relationships, but has a single function and cannot perform large-scale calculations, and metadata record confusion

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