Cross-Repository MDM Linking While Preserving Data Isolation
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Solution Overview
Problem
In enterprise computing environments, managing large quantities of data assets from distinct entities while ensuring data security, integrity, and compliance is cumbersome due to the complexity of maintaining separation and preventing unauthorized data sharing.
Innovation Solution
A system and method for managing Master Data Management (MDM) data sets using a primary computing system that maintains separation between distinct data repositories, prevents unauthorized data sharing, and creates cross-reference identifiers for patients across MDM data sets, ensuring data integrity and compliance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple MDM data sets are stored in separate data repositories to maintain data integrity and security, then data isolation and compliance are improved, but system complexity and difficulty of managing commonalities increase
Solution Approach 1:
The system segments data storage by maintaining separate MDM data sets in distinct data repositories (first data repository, second data repository, etc.), ensuring that each repository maintains its own data integrity and security. This segmentation allows multiple entities to store their data independently while the event-driven architecture coordinates them through standardized events, resolving the contradiction between data isolation and system complexity.
Solution Approach 2:
The system introduces an event-driven architecture as an intermediary layer that mediates between separate data repositories. Events are published to a communication platform that enables discovery and association across repositories without direct access. This intermediary mechanism allows coordinated data management while preserving repository separation, addressing both data integrity and system complexity concerns.
2Reliability
If data repositories are kept separate to prevent unauthorized data sharing, then data security is improved, but ability to identify and associate common patient records across entities deteriorates
Solution Approach 1:
The system extracts only the essential identification information needed for patient association while keeping detailed data in separate repositories. Events contain minimal necessary information (such as patient identifiers) that can be shared across the communication platform without exposing sensitive data. This extraction approach maintains security while preserving the ability to identify and associate patient records across entities.
Solution Approach 2:
The communication platform acts as an intermediary that enables patient record association across separate repositories. Through standardized events published to this platform, entities can discover and link patient records without direct repository access. This intermediary mechanism preserves data security while preventing loss of patient association information through event-based coordination.
3Adaptability or versatility
If MDM data sets are not combined but kept separate, then compliance and data integrity are maintained, but operational complexity of managing commonalities increases
Solution Approach 1:
The event-driven architecture enables continuous automatic coordination between separate MDM data sets. When changes occur in one repository, events are continuously published and processed by other entities, maintaining data consistency without manual intervention. This continuous automated operation maintains compliance while reducing the operational complexity of managing commonalities across separate repositories.
Solution Approach 2:
Each data repository operates independently and publishes events based on its own data changes, enabling self-service coordination. Entities automatically discover and process relevant events from other repositories without requiring centralized management or manual configuration. This self-service approach maintains compliance with separate repository requirements while simplifying the management of commonalities through automated event processing.
Data Source
AI summary
A method for managing Master Data Management (MDM) data sets is provided. The method stores a second MDM data set into a second data repository separate and distinct from a first data repository storing a first MDM data set; continuously protects data integrity of the first and second MDM data sets, by: (i) maintaining separation between the first data repository and the second data repository, and (ii) preventing unauthorized data sharing by the first and second MDM data sets; detects a change to an MDM record of the first MDM data set, via a communication platform; determines that the second MDM data set includes a second MDM record associated with the patient, based on recognition of the patient by the second data repository; creates a cross-reference identifier for the patient; and updates the first MDM data set and the second MDM data set to include the cross-reference identifier.