Hierarchical Master Data Sync With Override-Based Update Routing
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Solution Overview
Problem
Large enterprises face challenges in managing large volumes of data across multiple applications without hard-coded custom connections, leading to out-of-date data and inefficiencies in data synchronization.
Innovation Solution
A data synchronization system that accesses multiple data sets, receives subscriptions, determines candidate values, and stores override metadata to ensure data accuracy by triggering modifications based on updates across applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If applications store data locally without centralized synchronization, then each application maintains data independence and avoids complex connections, but data becomes out-of-date and data consistency deteriorates
Solution Approach 1:
The patent introduces a data synchronization system as an intermediary component that mediates between multiple applications with local data storage. This synchronization system subscribes to data changes in source applications and publishes updated data to subscriber applications, enabling data consistency without direct connections between applications. The intermediary handles the complexity of data routing, subscription management, and update coordination, isolating applications from synchronization complexity while maintaining reliable data consistency.
2Reliability
If hard-coded custom connections are established between applications for data sharing, then data accuracy improves, but system complexity and maintenance difficulty increase significantly
Solution Approach 1:
The patent implements a universal data synchronization system that serves multiple applications simultaneously through standardized subscription and publication mechanisms. Instead of creating unique hard-coded connections for each application pair, the synchronization system provides a multi-functional platform that handles data sharing across numerous applications using common protocols and interfaces. This universal approach maintains data accuracy through systematic update propagation while dramatically reducing connection architecture complexity.
Solution Approach 2:
The synchronization system creates and manages data copies between applications rather than establishing direct connections. When data changes occur in a source application, the synchronization system copies the updated data to subscriber applications. This copying mechanism ensures data accuracy is maintained across applications without requiring complex inter-application connections, as each application receives standardized data copies through the synchronization intermediary.
3Productivity
If applications independently manage their own data without subscriptions, then system operation simplicity improves, but data update timeliness and information freshness deteriorate
Solution Approach 1:
The patent implements a feedback mechanism where the data synchronization system subscribes to data change notifications from source applications and automatically triggers data propagation when changes occur. This feedback loop ensures that data updates are detected and propagated in real-time or near-real-time across the system. The subscription management system monitors data changes, receives feedback about updates, and automatically initiates synchronization actions, maintaining high data update timeliness while managing subscription complexity through automated processes.
Data Source
AI summary
A data synchronization system accesses a plurality of data sets. The system receives a subscription from a third application to a first data set of a first application. When the system receives a notification of an update to a first item of the first data set, and determines via a mapping within the subscription, a value to use as a version of the first field for a corresponding item of a third data set. When the system receives input overriding the first mapping to determine values from a first field of the second data set, the system stores override metadata indicating the second data set is a data source for the third data set. After the mapping is overridden, when receiving a notification of an update to the second data set, the system triggers a modification to the first corresponding item based on the update to the second corresponding item.