Virtual Directory for Unified Data Repository Management
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Solution Overview
Problem
Existing systems fail to provide a unified view or aggregation of data across multiple domains, leading to inconsistencies and difficulties in updating information across various repositories, which can result in incomplete or inappropriate updates, affecting data consistency and system performance.
Innovation Solution
A system that uses a virtual directory to provide a shared view of data across multiple domains, allowing for updates to be managed through a single access point, which aggregates and synchronizes data across repositories, and launches business processes to ensure all necessary updates are executed, using a unified user profile and identity management to handle different identities and data sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is stored in multiple separate repositories across different domains, then each repository can maintain its own data model and schema independently, but data consistency and synchronization across repositories become difficult to maintain
Solution Approach 1:
The patent introduces a workflow engine as an intermediary between multiple data repositories. This workflow engine coordinates data updates across repositories by executing predefined workflows that ensure consistency. When data needs to be updated across multiple domains, the workflow engine manages the synchronization process, acting as a mediator that maintains reliability without requiring a centralized data model.
Solution Approach 2:
The system segments data storage into multiple independent repositories while introducing a unified access interface layer. Each repository maintains its own schema and data model independently, but the unified interface provides consistent access patterns. This segmentation allows each domain to adapt its data model independently while the overall system maintains consistency through the coordinated access interface.
2Reliability
If a unified view of data across multiple domains is implemented, then data consistency can be maintained, but system complexity increases due to the need for coordination mechanisms
Solution Approach 1:
The workflow engine is designed as a universal component that handles multiple functions: data coordination, consistency validation, update scheduling, and cross-domain communication. By creating a single multi-functional component rather than separate mechanisms for each consistency requirement, the system achieves data consistency without proportionally increasing complexity.
Solution Approach 2:
The system implements feedback mechanisms where the workflow engine continuously monitors data state across repositories and automatically triggers corrective workflows when inconsistencies are detected. This closed-loop feedback system maintains consistency automatically, reducing the need for complex manual coordination mechanisms and lowering overall system complexity.
3Reliability
If data updates are propagated across all repositories simultaneously, then data consistency is maintained, but update time and system performance deteriorate
Solution Approach 1:
Instead of simultaneous propagation, the system uses periodic workflows that update repositories in scheduled sequences. The workflow engine executes updates at periodic intervals across different repositories based on predefined schedules and dependencies. This periodic action maintains consistency while allowing time for each update operation, preventing performance deterioration from simultaneous updates.
Solution Approach 2:
The system performs preliminary validation and preparation actions before actual data propagation. Workflows are predefined and validated in advance, with dependency relationships established beforehand. When an update is needed, the system executes pre-planned sequences rather than determining updates in real-time, which reduces the time required for propagation while maintaining consistency.
4Adaptability or versatility
If multiple access points are provided for different domains, then domain autonomy is maintained, but data manipulation becomes complex and error-prone
Solution Approach 1:
The patent merges multiple domain-specific access points into a single unified access interface. This unified interface provides consistent methods for data manipulation across all domains, hiding the complexity of domain-specific variations. Users interact with a single standardized interface rather than multiple domain-specific interfaces, which simplifies operation while maintaining the underlying domain autonomy through the workflow coordination layer.
Data Source
AI summary
A data repository includes information for multiple data systems, which can each control data in this and a number of other domains. A business process can be launched by one of the data systems to update the target data and any related data in the repository or any other related repository. Any request to update data is intercepted and the business process can launch workflows and apply policies as needed to process the request. Workflows can be associated with the fields being updated or process being executed, such that any update to the target data is also accurately reflected in any other related system. Further, launching a workflow allows processes to be run before the data is updated, such that the data can be modified, added to, rejected, or otherwise processed before being added to the appropriate repositories.