Conflict Rule System for Multi-Source Data Integration
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Solution Overview
Problem
When data from multiple sources contains conflicting values for a data element, there is a risk of overwriting correct data with incorrect data, as existing solutions lack effective methods to manage and resolve these conflicts.
Innovation Solution
Implementing a conflict rule system that determines the main data value by defining automatic, semi-automatic, or manual procedures for resolving conflicts, allowing users to configure rules for each data element, and storing the conflict rule with the data value to maintain a record of derivation and enable modifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data from multiple sources is compiled and stored in a single location, then data integration is achieved, but the risk of overwriting correct data with incorrect data increases
Solution Approach 1:
The system performs preliminary conflict detection and resolution before data is permanently stored. By identifying potential conflicts between data values from different sources and applying resolution rules in advance, the system prevents incorrect data from being written to the consolidated storage, thus maintaining data accuracy while achieving integration.
Solution Approach 2:
The patent introduces an intermediary conflict resolution mechanism that sits between data ingestion and final storage. This intermediary layer evaluates conflicting data values, applies resolution strategies (such as source priority, recency, or custom rules), and determines which value should be stored, thereby protecting against data overwriting errors.
2Reliability
If a conflict resolution system is implemented, then data accuracy is improved, but system complexity increases
Solution Approach 1:
The conflict resolution system is segmented into distinct functional components: data reception modules, conflict detection modules, rule evaluation modules, and storage modules. Each component handles a specific aspect of the data integration process, making the overall system more manageable and maintainable despite the added complexity of conflict resolution.
Solution Approach 2:
The system uses configurable parameters and resolution rules that can be adjusted without changing the underlying system architecture. By parameterizing the conflict resolution logic (such as source priority weights, time-based rules, or domain-specific criteria), the system maintains flexibility and adaptability while keeping the core structure relatively simple.
3Adaptability or versatility
If multiple conflict rules are configured for different data elements, then resolution flexibility is improved, but configuration complexity increases
Solution Approach 1:
The patent implements a universal conflict resolution framework that can handle multiple types of conflicts across different data elements using a common set of resolution rules and strategies. This multi-functional approach allows the same system infrastructure to resolve conflicts in various data domains (e.g., numerical, categorical, temporal) without requiring completely separate rule sets for each data type.
Solution Approach 2:
While maintaining a universal framework, the system allows for local customization of resolution rules specific to particular data elements or sources. Each data element can have tailored conflict resolution criteria (such as source-specific priorities or element-specific validation rules) applied within the broader universal framework, balancing flexibility with manageability.
Data Source
AI summary
A solution for managing data received from multiple sources is provided. In particular, when conflicting data values are received from multiple sources for a data element, a conflict rule is used to determine the main data value for the data element, which is subsequently stored for use. The conflict rule can define any automatic, semi-automatic, or manual procedure for resolving the conflict. The conflict rule, or an identifier thereof, can be stored with each data value and the main data value for the data element.