Adapting Data Quality Rules via Editable Widgets
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing data quality systems cannot easily modify data quality rules at runtime, requiring changes to application or source system code, which is time-consuming and inflexible, especially when different applications have varying data quality requirements.
Innovation Solution
A system and method that allows data quality rules to be adjusted using editable widgets, enabling customization of data quality rules for specific applications by applying a common set of predefined rules and modifying them as needed, facilitating adaptation based on user specifications and application requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data quality rules are established by application or source system code, then data quality can be ensured for each application, but the rules cannot be modified at runtime and require code changes
Solution Approach 1:
The patent implements dynamic data quality rules that can be modified at runtime without code changes. The system allows rules to be adjusted during operation through a configurable interface, enabling the rules to adapt to changing application requirements while maintaining data quality assurance
Solution Approach 2:
The patent establishes a framework where data quality rules are pre-configured and validated before deployment, but designed to be easily adjustable afterward. The preliminary setup ensures initial data quality while the architecture prepares for future modifications without requiring code changes
2Ease of manufacture
If general data quality rules are established, then data formatting can be ensured, but precise data quality for specific applications cannot be guaranteed
Solution Approach 1:
The patent implements local quality by allowing different data quality rules to be applied to different applications or data sources. Each application can have customized rules tailored to its specific requirements while still using the same underlying system, ensuring precise data quality for each local context
Solution Approach 2:
The patent segments the data quality rule system into modular, application-specific rule sets. This segmentation allows general formatting rules to be maintained while enabling application-specific precision through separate, configurable rule modules that can be independently adjusted
3Stability of the object's composition
If data quality rules are changed after processing cycle, then system stability is maintained, but changes require time-consuming code modification
Solution Approach 1:
The patent enables dynamic rule modification at runtime without system restart or code changes. The system maintains stability through controlled rule updates that are validated before application, allowing quick adaptation while preserving overall system integrity
Solution Approach 2:
The patent uses template-based rule copying where standardized data quality rule templates can be quickly replicated and customized for different applications. This copying mechanism reduces modification time by reusing proven rule structures rather than creating rules from scratch
Data Source
AI summary
During application of data quality rules to a data set obtained from a data source, data is retrieved from the data source along with a common set of rules configured to format the retrieved data in a manner in accordance with one or more predefined data quality rules of the common set of rules. At least one predefined data quality rule is adjusted utilizing at least one editable widget to form a modified set of data quality rules adapted for use with a specified application. The modified set of data quality rules is applied to the retrieved data.