Automated Statistical Data Validation System
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Solution Overview
Problem
Manual review of large quantities of statistical data is time-consuming and labor-intensive, leading to delays in identifying errors and issues, as existing methods lack efficient automated validation processes.
Innovation Solution
An automated system and process for validating statistical data outputs using a dual looping structure, which applies predefined or automatically derived validation cases to determine pass/fail results, incorporating machine learning to improve validation set creation and enabling real-time or periodic validation with notifications for errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual review of statistical data is performed, then data validation can be conducted, but it is time-consuming and labor-intensive
Solution Approach 1:
The patent replaces the manual mechanical review process with an automated computer-based system that uses algorithms and machine learning models to validate statistical data, thereby eliminating the time-consuming and labor-intensive nature of manual review while maintaining validation effectiveness
Solution Approach 2:
The system enables self-service validation where the computer automatically performs data validation tasks without requiring manual intervention, using predefined validation rules and automated analysis methods to identify errors and issues in statistical data
2Measurement precision
If manual review of statistical data is performed, then errors can be identified, but significant delays occur in identifying issues
Solution Approach 1:
The patent implements continuous automated validation that operates without interruption, allowing the system to constantly monitor and validate statistical data as it is generated, thereby eliminating the delays inherent in periodic manual review cycles while maintaining precise error detection capabilities
3Productivity
If automated validation system is implemented, then review time is reduced, but system complexity increases
Solution Approach 1:
The patent segments the validation system into distinct modular components including data ingestion modules, validation rule engines, machine learning models, and reporting modules, allowing each component to perform specific functions independently and making the overall complex system more manageable and maintainable
Data Source
AI summary
A system and method are provided for validating data. The method is executed by a device having a data interface coupled to a processor and includes obtaining a validation set comprising at least one validation case, each validation case comprising at least one test condition. The method also includes obtaining, via the data interface, at least one data set to be validated using the validation set. The method also includes applying the validation set to the at least one data set to validate the data in the data set by, for each record in the at least one data set, validating a value in the record according to the at least one test condition. The method also includes outputting a validation result for each record.