Intelligent data governance cleaning method and device based on knowledge graph
By constructing a data cleaning graph database and performing semantic recognition, cleaning scripts are automatically generated, solving the problems of high cost and low efficiency caused by manually writing scripts, and achieving efficient and accurate data cleaning.
CN121901210APending Publication Date: 2026-04-21SHANGHAI XILING INFORMATION TECH CO LTD
0 Cites 0 Cited by
Patent Information
- Application Number
- CN202610028699.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-01-09
- Publication Date
- 2026-04-21
AI Technical Summary
Technical Problem
Existing data cleaning technologies rely on manually written cleaning scripts, resulting in high labor costs, low cleaning reliability, and low efficiency.
Method used
Construct a data cleaning graph database to store the cleaning mapping information of standard data tables and their fields. Automatically generate cleaning scripts through semantic recognition to realize the mapping between fields and cleaning methods.
Benefits of technology
It simplifies the process for data governance engineers, reduces labor costs, and improves the efficiency and accuracy of data cleaning.
✦ Generated by Eureka AI based on patent content.
Abstract
The invention discloses an intelligent data governance cleaning method and device based on a knowledge graph, and the method comprises the steps: constructing a data cleaning graph database which comprises a plurality of standard data tables and cleaning mapping information corresponding to each standard field in each standard data table, and combining the semantic recognition and table name recognition of a to-be-cleaned table; determining cleaning mapping information corresponding to each effective field in the to-be-cleaned table; then, a cleaning script can be automatically generated based on the determined cleaning mapping information; therefore, the cleaning script of the metadata and the data items in the production library can be automatically generated under the condition that the cleaning script does not need to be written manually, the operation process of data management engineers on data item standardization is effectively simplified, the difficulty of cleaning operation and the labor cost are reduced, and the efficiency and the accuracy of data cleaning are improved; therefore, the method is very suitable for large-scale application and popularization.
Need to check novelty before this filing date? Find Prior Art