Genworth Financial. has been granted a patent for a Metadata-Driven Data Quality Framework and Engine. This system dynamically generates code to assess data quality using metadata, integrating into data governance processes to enhance understanding and automate quality assessments based on defined rules and characteristics. GlobalData’s report on Genworth Financial gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Genworth Financial, was a key innovation area identified from patents. Genworth Financial's grant share as of July 2024 was 33%. Grant share is based on the ratio of number of grants to total number of patents.
Metadata-driven data quality framework and engine
The granted patent US12050568B2 outlines a system and method for implementing a metadata-driven data quality framework. This framework includes an input interface that receives requests for data quality rules along with specific characteristics of data quality, such as completeness, timeliness, consistency, and conformity. The system features a metadata repository that stores metadata at a physical element level, and a data quality engine that processes the input to generate data quality requirements. The engine performs an API read of the metadata repository to collect various types of metadata, including data quality rules, dataset details, and attribute types. It then processes this information to automatically generate code for the requested data quality rule, determining the appropriate data processing scheme based on the complexity of the rule and the data volume profile. The system also identifies a predetermined schedule for executing the data quality rule and stores the results for user access.
Additionally, the patent specifies that the data quality rules can be either canned or custom, with the latter being processed using relevant metadata and rule details. The execution schedule can vary from daily to yearly, depending on the frequency specified. The framework allows for user interaction, enabling data users to provide feedback on the technical metadata presented through a user interface. This comprehensive approach aims to enhance data quality management by automating the generation and execution of data quality rules, thereby improving the efficiency and effectiveness of data governance practices.
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