Data Artifact Integration via Consolidation Configuration
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Solution Overview
Problem
Existing technologies face challenges in effectively integrating data from multiple instances of a data artifact, particularly in complex software use scenarios where data may be disjoint or overlap partially, leading to ambiguity in how data should be combined.
Innovation Solution
The proposed solution involves creating a data artifact that references a consolidation artifact, with configuration information indicating how data from multiple instances of a data artifact should be integrated. This includes modifying data requests based on the configuration information to ensure accurate data retrieval from the consolidation artifact.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If data from multiple instances of a data artifact is integrated without configuration information, then data retrieval is simple, but data integration accuracy deteriorates due to ambiguity in how data should be combined
Solution Approach 1:
The patent introduces configuration information as a parameter that defines how data from multiple instances should be integrated. This configuration includes parameters such as integration mode (union, intersection, difference), instance identification, and data artifact identification, which transform the data retrieval process from a simple operation to a configurable one that maintains both simplicity and accuracy.
2Measurement precision
If configuration information is added to data artifacts to control data integration, then data integration accuracy improves, but device complexity increases
Solution Approach 1:
The configuration information is prepared in advance and attached to the data artifact before data retrieval operations. This preliminary action includes defining the integration mode, identifying instances and data artifacts, and establishing the rules for data combination, which eliminates the need for complex runtime decision-making processes.
3Quantity of substance
If data from multiple instances is always integrated, then data completeness improves, but loss of time increases due to processing overhead
Solution Approach 1:
The patent implements dynamic data integration where the integration behavior is determined by the configuration information attached to each data artifact. The system dynamically selects which instances to integrate and how to combine their data based on the specific configuration, rather than always integrating all instances, thus optimizing processing time while maintaining data completeness when needed.
4Measurement precision
If configuration information specifies exact integration rules, then data integration precision improves, but adaptability deteriorates when dealing with different software use scenarios
Solution Approach 1:
The configuration information structure is designed to be universal and applicable across different software use scenarios. It includes flexible parameters such as integration mode (union, intersection, difference), instance identification, and data artifact identification that can be configured to suit various scenarios including single-instance operations, multi-instance operations, and different integration strategies, making the system adaptable while maintaining precision.
Data Source
AI summary
The present disclosure provides techniques and solutions for integrating data from different instances of a data source, such as a data artifact. That is, in some cases data may be disjoint, or it may overlap in whole or part. How data should be integrated can depend on whether data overlaps, or a type or extent of overlap. An artifact that consumes data can be integrated to indicate how data from underlying instances of a data source should be integrated, including when this consuming artifact requests data indirectly from a consolidation artifact. A search against the consuming artifact can be modified based on configuration information in the consuming artifact indicating how or if data from multiple instances of the data source should be integrated.