A big data governance system and method based on a hierarchical label system

By using a big data governance system based on a hierarchical tagging system, the problem that existing tagging systems cannot adapt to business changes and cross-industry applications has been solved. This system enables accurate data classification and management, improves data processing efficiency and security, and ensures the stability and adaptability of the tagging system.

CN120596475BActive Publication Date: 2025-12-23BEIJING GUOXINDA DATA TECH CO LTD
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Patent Information

Application Number
CN202511086174.9
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-08-05
Publication Date
2025-12-23
Estimated Expiration
2045-08-05

AI Technical Summary

Technical Problem

Existing labeling systems cannot flexibly adapt to changes in business scenarios and cross-industry application needs, resulting in inaccurate data classification and insufficient accuracy in matching labels with data. Traditional data governance methods are unable to meet enterprises' stringent requirements for data quality and security, and lack real-time monitoring and dynamic repair mechanisms, leading to chaotic data management.

Method used

A big data governance system based on a hierarchical tagging system is adopted, including data access preprocessing, tag modeling and hierarchical configuration, tag parsing and data binding, tag-driven data governance, and tag conflict detection and dynamic update units. Through multi-mode matching algorithm, hash comparison and path traversal algorithm, the system achieves accurate data parsing, binding and real-time monitoring, and dynamically adjusts the tagging system.

Benefits of technology

It has enabled precise classification and management of data, improved data processing efficiency and accuracy, ensured data quality and security, reduced data governance costs, and ensured the stability and adaptability of the labeling system.

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Abstract

The application belongs to the technical field of big data management, and discloses a big data management system and method based on a layered label system, which comprises a data access preprocessing unit, a label modeling and layered configuration unit, a label analysis and data binding unit, a label-driven data management unit, and a label conflict detection and dynamic updating unit. The label-driven data management unit is triggered by the label binding result, the management rules are loaded through a dynamic rule engine, and the data is cleaned, classified, and safely protected by using a multi-dimensional verification strategy and an encryption control mechanism. The label conflict detection and dynamic updating unit monitors the label system in real time, adjusts and repairs conflicts by means of path traversal and version management technology, and ensures the stability of the label system. The two units jointly automatically process abnormal data, maintain the label system, and guarantee data quality and safety.
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