Data quality audit method based on database schema

A technology of data quality and database, applied in data processing applications, electrical digital data processing, special data processing applications, etc., can solve problems such as data anomalies, achieve the goal of strengthening measurement management capabilities, improving measurement work quality, and improving measurement work efficiency Effect
CN102609537AInactive Publication Date: 2012-07-25ELECTRIC POWER RES INST OF GUANGDONG POWER GRID
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Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Applications(China)
Current Assignee / Owner
ELECTRIC POWER RES INST OF GUANGDONG POWER GRID
Publication Date
2012-07-25
Estimated Expiration
Not applicable Β· inactive patent

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Abstract

The invention discloses a data quality audit method based on a database schema. The data quality audit method comprises a preprocessing module, a gathering module, a KPI (key performance indicator) processing module, an alarm information warehousing module and a KPI information warehousing module. With the adoption of the data quality audit method, data abnormalities caused by various complex reasons appearing in the data extraction process are solved. According to the data quality audit method, all data needing to be focused on are monitored in real time, various abnormal data are fast monitored, fast positioned and accurately alarmed, and the reliability, the usability and the authenticity of system data are improved.
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Description

technical field

[0001] The invention relates to the technical field of data quality auditing, in particular to providing a data quality auditing method based on a rule parser in a database mode. Background technique

[0002] In the massive power metering data, through the establishment of a data warehouse or data mart system, the massive concentration, calculation, data mining, and predictive analysis of various data can be realized. And these basic source data are generally considered to be correct. However, in the actual process, we found that through the analysis of the province's metering automation master station system, there may be data anomalies and errors in the process of data collection, data uploading, and final data intermediate calculation of each source data. For example: the master station metering data is missing due to the inability to collect remote terminal data, or the availability and reliability of system data is reduced due to business management and...

Claims

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