Configurable Dataflow for Enterprise System Integration
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Integrating data processing systems across different enterprises is challenging due to differences in data formats, interfaces, and signatures, leading to complex and costly solutions that are difficult to maintain and extend.
Innovation Solution
A system utilizing configurable data flows and modular integration entities to map objects between systems, allowing for seamless integration with minimal coupling, using workflows to configure data flows that can be easily adapted and reused, and handling communication retries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional integration methods are used to connect data processing systems with different formats and interfaces, then integration functionality is achieved, but system complexity and maintenance difficulty increase significantly
Solution Approach 1:
The patent introduces an integration entity as an intermediary component that mediates between the first data processing system and the second data processing system. This integration entity handles the complexity of format conversion, interface adaptation, and signature mapping, allowing the core systems to remain simple while achieving versatile integration capability.
Solution Approach 2:
The integration architecture is segmented into distinct modular components: the first data processing system, the integration entity, and the second data processing system. Each component has a specific responsibility, with the integration entity handling transformation logic. This segmentation isolates complexity to the integration layer while keeping individual systems simple and maintainable.
2Adaptability or versatility
If custom integration solutions are developed for each system pair, then specific integration requirements are met, but development time and cost increase
Solution Approach 1:
The integration entity is designed as a universal component that can handle multiple integration scenarios through configuration rather than custom development. It supports various data formats, interfaces, and signatures through a standardized transformation framework, allowing the same integration entity to serve multiple system pairs without requiring separate custom solutions for each.
Solution Approach 2:
The integration entity uses configurable parameters to adapt to different integration requirements. By changing configuration parameters such as data format specifications, interface definitions, and mapping rules, the same integration entity can be quickly adapted to different system pairs, eliminating the need for time-consuming custom development while maintaining flexibility.
3Adaptability or versatility
If multiple data processing systems are integrated, then system interoperability improves, but the difficulty of maintaining and extending the integration increases
Solution Approach 1:
The integration architecture segments maintenance responsibilities by isolating transformation logic within the integration entity. This allows maintenance activities to be focused on the integration layer without affecting the core data processing systems. Each integration entity can be independently updated, configured, or repaired, improving maintenance ease while supporting multiple system integrations.
Solution Approach 2:
The integration entity acts as a mediator that shields the core data processing systems from integration complexity. When maintenance or extensions are needed, changes are made to the integration entity's configuration or code without requiring modifications to the integrated systems themselves, thereby improving ease of repair and extension while maintaining high interoperability.
Data Source
AI summary
A system generates a first data set by executing, in response to occurrence of an event, a data flow configured with a property of a first object of a first data processing system to map the first object to a second object of a second data processing system. The system acquires additional information, including additional properties of the first object and data used by the first and second data processing systems to communicate with other data processing systems, from the first and second data processing systems to map the first object to the second object. The system generates a second data set having a format compatible with the second data processing system based on the first data set and the additional information and sends the second data set to the second data processing system. The system maps other objects using reconfigured data flows.