PROCESS AND METHOD FOR DATA ASSURANCE MANAGEMENT BY APPLYING DATA ASSURANCE METRICS
First Claim
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1. A data filtering method comprising:
- receiving data from a database;
determining if the data is valid by utilizing rules in a data hygiene engine, wherein the rules are;
(1) at least one rule selected from the group consisting of;
field rules, row rules, groups of rows rules, and combinations thereof, and(2) at least one data assurance management metrics rules, wherein the data assurance management metrics rules are data quality metric rules used to analyze groups of rows based on user requirements, wherein data quality metrics are calculated for groups of rows and compared to a threshold;
filtering invalid data;
outputting a production database without the invalid data.
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Abstract
The present invention relates generally to methods, software and systems for measuring and valuing the quality of information and data, where such measurements and values are made and processed by implementing objectively defined, measurable, comparable and repeatable dimensions using software and complex computers. The embodiments include processes, systems and method for identifying optimal scores of the data dimension. The invention further includes processes, systems and method for data filtering to improve the overall data quality of a data source. Finally, the invention further includes processes, systems and method for data quality assurance of groups of rows of a database.
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Citations
20 Claims
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1. A data filtering method comprising:
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receiving data from a database; determining if the data is valid by utilizing rules in a data hygiene engine, wherein the rules are; (1) at least one rule selected from the group consisting of;
field rules, row rules, groups of rows rules, and combinations thereof, and(2) at least one data assurance management metrics rules, wherein the data assurance management metrics rules are data quality metric rules used to analyze groups of rows based on user requirements, wherein data quality metrics are calculated for groups of rows and compared to a threshold; filtering invalid data; outputting a production database without the invalid data. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20)
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Specification