Metadata-based data quality management method and system

Abstract

The invention provides a metadata-based data quality management method, comprising the steps: establishing a unified data model according to data in a database; configuring metadata according to the established data model; generating checking rules; configuring executive strategies, wherein each executive strategy is bound with one or more than one checking rule, automatically executing the strategies as planned, searching for a target data in the database and storing the target data; generating a report and issuing. According to the method, the enterprise data quality management is carried out on the basis of metadata, data integrity checking rules and data compliance checking rules are automatically generated through analyzing service and management characteristic results of metadata configuration, and beforehand prevention, in-service inspection and ex-post evaluation in data quality management are comprehensively supported by using an automatic method.

Description

technical field [0001] The invention relates to a data processing method, in particular to a metadata-based data quality management method and system. Background technique [0002] With the development of information technology, more and more data information is generated, and various data quality problems may be caused during the entire life cycle of data from planning, acquisition, storage, sharing, maintenance, application, and extinction. Wrong data will cause serious adverse consequences to the operation and decision-making of the enterprise, so data quality management has become a crucial link in the construction of enterprise informatization. [0003] At present, the industry lacks a complete data quality management solution, and database administrators usually need to write program scripts to identify problematic data. The advantage of this method is that it is simple and does not need to deploy additional systems. The disadvantage is that it is not standardized, po...

AI Technical Summary

Problems solved by technology

[0006] 1. Lack of unified management, the data management methods and methods of each business system or each branch company are quite different, and the level is uneven;

[0007] 2. The data source is not unique, data management is carried out according to the system boundary, data redundancy between systems leads to data multi-head management, and data consistency is poor;

[0008] 3. Responsibilities are unclear, and responsibilities for data management, entry, and use have not been assigned to specific departments and positions;

[0009] 4. There is a lack of unified modeling of enterprise resources, and the data models of enterprise resources such as human, financial, and material are not unified, which makes data integration and integration more difficult;

[0010] 5. The implementation of data standards is not in place, and the existing business systems have not been fully consolidated and complied with data specifications. There are phenomena of inconsistent information classification and coding, and inconsistent business meanings

Images