Master Data Mapping for Cross-System Querying
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Solution Overview
Problem
Existing systems face challenges in accurately and efficiently managing and retrieving master data associated with natural persons across multiple software systems and landscapes, leading to ambiguity and duplication of identifiers.
Innovation Solution
A data mapping technique is employed to construct a map of explicit and inferred connections between different data pieces across various databases and systems, using a parameter like a family name as a boundary condition, allowing for efficient querying and retrieval of relevant data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If master data is distributed across multiple software systems and landscapes, then system versatility and adaptability are improved, but data retrieval accuracy and efficiency deteriorate due to ambiguity and duplication of identifiers
Solution Approach 1:
The patent introduces a centralized master data management system that acts as an intermediary between multiple software systems and landscapes. This central system maintains a unified view of master data entities (customers, suppliers, employees) across distributed systems, resolving identifier ambiguity and duplication by providing a single source of truth that all systems can query and synchronize with.
Solution Approach 2:
The master data management system implements universal identifier schemes and standardized data models that work across all connected software systems and landscapes. This universal approach allows the same identifier to be recognized and used consistently across different systems, eliminating duplication and improving retrieval accuracy while maintaining system versatility.
2Adaptability or versatility
If master data entities are widely distributed across multiple software systems, then system independence and flexibility are improved, but query execution efficiency and resource consumption worsen
Solution Approach 1:
The system performs preliminary actions by pre-establishing a centralized registry of master data entities and their relationships across multiple systems. Query optimization is prepared in advance by creating execution plans that leverage this pre-organized structure, allowing efficient retrieval without scanning all distributed systems for each query.
Solution Approach 2:
The patent segments the distributed system landscape into manageable units with a centralized coordination layer. Each software system maintains its local data with independence, while the central master data management system segments and organizes the global view of entities, enabling efficient queries by directing searches to specific segments rather than all systems.
3Adaptability or versatility
If multiple representations of natural persons are maintained across different systems, then system-specific data requirements are satisfied, but data consistency and reliability deteriorate
Solution Approach 1:
The master data management system implements feedback mechanisms where changes to master data entities in any connected system are automatically propagated back to the central registry and synchronized to other systems. This feedback loop ensures that all systems maintain consistent views of master data while still allowing system-specific representations and requirements.
Solution Approach 2:
The patent merges multiple system-specific representations of natural persons into a unified master data model at the central management system. This merging process consolidates duplicate entities, resolves conflicts through standardized rules, and creates a single reliable source of truth that all systems can reference while maintaining their own adapted representations.
Data Source
AI summary
Embodiments permit searching across different system landscapes, for data associated with master data objects. A map is constructed comprising (explicit, inferred) connections between different pieces of data located in various databases, systems, and landscapes. In certain embodiments the map is constructed utilizing a parameter (e.g., family name) present in a received query, as a boundary condition. The map may be in tabular form, and may conform to a particular notation scheme. Once the map is constructed, the query is executed thereupon to search for relevant data. The corresponding query result is received and stored, ultimately for communication back to the user posing the original query. Embodiments may be particularly suited to returning private data of a unique entity (e.g., natural person, corporation, juristical person) that is stored over a variety of different master data objects (e.g., employee, customer, supplier) and across complex system landscapes.


