Data quality detection method and apparatus, electronic device, and computer-readable medium
By generating a target network and combining node centrality scores and quality control rules, the problem of unconsidered data node relationships in big data platforms is solved, enabling more accurate data quality detection and anomaly discovery.
CN119766680BActive Publication Date: 2026-05-29CHINA TELECOM CLOUD TECH CO LTD
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- CHINA TELECOM CLOUD TECH CO LTD
- Filing Date
- 2024-11-22
- Publication Date
- 2026-05-29
AI Technical Summary
Technical Problem
In existing technologies, data quality detection methods fail to fully consider the relationships and mutual influences between data nodes in big data platforms, resulting in inaccurate detection.
Method used
Based on the data nodes and their relationships within the big data platform, a target network is generated. By using node centrality scores and quality control rules, the quality control results of the data nodes are determined, ultimately evaluating the overall data quality of the big data platform.
Benefits of technology
It improves the accuracy of data quality detection, enabling the identification of key issues and anomalies, and ensuring the high-quality operation of the data processing chain and applications.
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Smart Images
Figure CN119766680B_ABST
Abstract
Embodiments of the present application disclose a data quality detection method and device, electronic equipment and a computer readable medium. The embodiments of the method comprise: generating a target network based on data nodes in a big data platform and the association relationship between the data nodes; determining the node centrality score of each data node in the target network based on the network structure of the target network; determining the first quality detection result of each data node in the target network based on the preset quality inspection rule and the attribute information of each data node in the target network; determining the second quality detection result of each data node in the target network based on the node centrality score and the first quality detection result of each data node in the target network; and determining the data quality detection result of the big data platform based on the second quality detection result of each data node in the target network. The implementation improves the accuracy of data quality detection.
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