Projector and Selector Components for Data Integration Mapping
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Solution Overview
Problem
Existing data integration systems require explicit definition of all input and output attributes in mappings, leading to cumbersome design and maintenance due to the need for attribute-level connectors and explicit attribute management.
Innovation Solution
The data integration system employs projector and selector component types that allow for attribute propagation and inheritance from upstream components, reducing the need for explicit attribute management and simplifying the design process by enabling component-level connectors and rerouting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If explicit attribute definition is used in data integration mappings, then data accuracy and completeness are improved, but design complexity and maintenance burden increase
Solution Approach 1:
The mapping system automatically determines attribute visibility and connectivity requirements based on component types and data flow patterns, eliminating the need for manual attribute-level configuration. The system serves itself by inferring necessary attributes from upstream components and propagating them automatically through the mapping pipeline.
Solution Approach 2:
The patent introduces universal component types (projector and selector) that can handle multiple attribute propagation scenarios without requiring specific configuration for each case. These components provide multi-functional attribute management capabilities that work across different data integration contexts.
2Reliability
If explicit attribute management is implemented, then data integration reliability is improved, but ease of operation deteriorates
Solution Approach 1:
The system automatically manages attribute visibility and connectivity by analyzing component types and data flow patterns, eliminating manual attribute management tasks. Users simply configure high-level mapping logic while the system handles attribute propagation and connectivity determination automatically.
Solution Approach 2:
The patent performs preliminary determination of attribute visibility and connectivity requirements based on component types before actual data integration execution. This advance preparation ensures reliability while keeping the user interface simple, as the complex attribute management is resolved during mapping design rather than during operation.
3Manufacturing precision
If attribute-level connectors are used, then data mapping precision is improved, but maintenance difficulty increases
Solution Approach 1:
The patent merges multiple attribute-level connector configurations into unified component-level connections. By combining attribute management at the component level rather than requiring individual attribute connectors, the system maintains precise data mapping while dramatically simplifying maintenance operations.
Solution Approach 2:
The system creates template-based component definitions that automatically replicate attribute propagation patterns across multiple mappings. Once a component type is defined with its attribute visibility rules, these rules are copied and applied consistently throughout the data integration pipeline, ensuring precision while reducing maintenance burden.
4Loss of information
If all attributes are declared explicitly from start to end, then data flow completeness is improved, but design time increases
Solution Approach 1:
The system automatically determines and propagates necessary attributes through the data flow based on component types and downstream requirements, eliminating the need for manual declaration of all attributes from start to end. The system serves itself by inferring attribute requirements and propagating them automatically.
Solution Approach 2:
The patent performs preliminary analysis of component types to determine attribute visibility requirements before full mapping design is completed. This allows the system to pre-establish attribute propagation paths based on component characteristics, reducing the time needed for complete attribute declaration while ensuring data flow completeness.
Data Source
AI summary
A data integration system is disclosed that incorporates one or more techniques for simplifying the design and maintenance of a mapping. As components are added or removed to an existing design, the data integration system removes the need to specify all input and output attributes. In one aspect, components types are implemented that allow assignment expressions to reference all or part of upstream components. Therefore, attributes of certain types of components can be propagated to downstream components or otherwise inherited from upstream components with minimal effort on the part of a map designer. During code generation the attributes required to be projected by any component can be derived based on the needs of the downstream components.