GUI Validator Configuration for Data Quality Checking
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Solution Overview
Problem
Conventional data validation platforms require users to manually input parameters and routines in a specific computer or logical language, lacking technical knowledge to properly extract desired statistics and validate data effectively.
Innovation Solution
A system that allows users to select and customize validators through a graphical user interface, applying validation parameters and routines to data sets, generating data quality reports based on the validation results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users manually input parameters and routines in a specific computer or logical language to create validators, then data validation capability is achieved, but the system becomes inaccessible to users lacking technical knowledge
Solution Approach 1:
The patent introduces a visual configuration interface that acts as an intermediary between users and the validation system. Users configure validators through graphical elements and drag-and-drop operations rather than directly coding, while the system translates these visual configurations into executable validation logic. This mediator layer shields users from technical complexity while maintaining full validation functionality.
Solution Approach 2:
The patent replaces the traditional mechanical approach of manual coding with a visual programming paradigm. Instead of requiring users to type and debug code in specific languages, the system uses graphical user interface elements, drag-and-drop operations, and visual configuration panels to define validation rules. This substitution transforms a text-based mechanical process into a more intuitive visual process.
2Ease of operation
If a visual configuration interface is implemented to improve ease of use, then accessibility for non-technical users is enhanced, but the interface and system complexity increase
Solution Approach 1:
The patent divides the validation configuration process into distinct modular sections: data source selection, validator type selection, parameter configuration, and rule definition. Each section is presented as a separate configurable module that users can interact with independently. This segmentation reduces perceived complexity by breaking down the overall task into manageable, discrete steps rather than presenting a monolithic complex interface.
Solution Approach 2:
The patent implements a universal visual configuration framework that handles multiple validator types and data sources through a single consistent interface paradigm. The same drag-and-drop mechanisms, configuration panels, and visual elements are reused across different validation scenarios, reducing the need for users to learn multiple interface languages while maintaining versatility across diverse validation needs.
Data Source
AI summary
Systems and methods are validating data in a data set. A data set including data to validate and a validator to use in validating the data is selected based on user input generated based on interactions of a user with a graphical user interface. The validator is applied to the data to determine whether one or more statistics generated through application of the validator to the data is valid or invalid based on a validation routine associated with the validator. A data quality report indicating whether the data set is valid or invalid, based on a determination of whether the one or more statistics is valid or invalid, is generated and selectively presented to the user through the graphical user interface.