Selective Data Transport for Model Updates
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Solution Overview
Problem
Managing large data models across networked computer systems is challenging due to storage and connectivity limitations, particularly for organizations with limited resources, as maintaining up-to-date models with acceptable response times is difficult.
Innovation Solution
A computer-implemented method for selective data transport that exports and imports data sets including model framework, option group, rule, and junction objects between data repositories, allowing for the updating of models, products, and solutions across different Salesforce organizations, with features like locking for exclusive write access, retrying failed transports, and versioning support.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If large data models are kept up-to-date and available in physical or network locations, then data accessibility and response time are improved, but storage capacity and network resources are overwhelmed
Solution Approach 1:
The patent segments the data model into multiple data sets (first data set with model framework, second data set with junction objects, third data set with properties). This segmentation allows selective transport of only necessary components, reducing overall storage requirements while maintaining accessibility of critical model elements.
Solution Approach 2:
The patent extracts and transports only the essential model components (framework, junction objects, and properties) from the source data repository to the target data repository. By taking out only the necessary data elements rather than transporting entire models, storage capacity is preserved while response time for accessing critical model data is improved.
2Manufacturing precision
If selective data transport is implemented with multiple data sets and junction objects, then model update accuracy is improved, but data transport complexity increases
Solution Approach 1:
The patent performs preliminary actions by exporting the model framework, junction objects, and properties in a specific sequence before transport. The first data set (model framework) is exported and transported first, followed by the second data set (junction objects), and then the third data set (properties). This preliminary structuring ensures that when data is imported at the target repository, the model is re-created with accurate relationships and attributes, improving model update accuracy while managing transport complexity through organized preprocessing.
3Adaptability or versatility
If data is transported between Salesforce organizations, then enterprise application capability is improved, but network bandwidth and connectivity resources are consumed
Solution Approach 1:
The patent applies partial action by transporting only the necessary portions of the data model (framework, junction objects, and properties) rather than complete model copies. This selective transport approach enables enterprise application capability across multiple Salesforce organizations by sharing essential model components, while consuming minimal network bandwidth. The system transports exactly what is needed—no more, no less—optimizing network resource utilization.
Data Source
AI summary
A method for updating a non-current data model using a current data model. The update exports a first data set which includes a file with a model object for the current data model, another with option group (“OG”) objects, another with rule objects, and another with junction objects that relate a rule to an OG. The update exports a second data set that includes a file with model-to-OG junction objects, and a file with model-to-rule junction objects. The update transports the first, and second data sets from a first data repository to a second data repository. The update imports, to the non-current data model, the first, and second data sets. The update recreates, in the non-current data model, the model-to-option-group junctions and the model-to-rule junctions.