Data Artifact Extension Propagation Across Database Systems
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Solution Overview
Problem
In complex software applications, particularly those using virtual data models, propagating extensions to data artifacts across different database systems, such as on-premise and cloud systems, is tedious, error-prone, and often requires manual replication, which can lead to inconsistencies and conflicts due to differing user permissions and access levels.
Innovation Solution
A method for automatically or semi-automatically propagating extension elements to related data artifacts by analyzing the type and context of the extension elements and applying predefined rules, ensuring that extensions are applied consistently across systems while considering user permissions and access levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual replication of extensions is performed across different database systems, then user control and permission management are maintained, but the process becomes tedious, error-prone, and time-consuming
Solution Approach 1:
The system performs preliminary analysis of extension elements and their compatibility with target artifacts before actual propagation. This includes evaluating user permissions, artifact types, and extension characteristics in advance to determine propagation eligibility, thereby preventing errors before they occur and reducing manual intervention needs
Solution Approach 2:
An intermediary propagation service is introduced between the source and target database systems. This service automatically manages the extension propagation process, including permission verification, conflict resolution, and error handling, thereby maintaining data consistency while eliminating manual replication tasks
2Productivity
If automatic propagation of extensions is implemented, then propagation speed and consistency are improved, but complexity in managing permissions and access levels increases
Solution Approach 1:
The system implements feedback mechanisms that automatically monitor propagation results, detect conflicts, and adjust propagation decisions based on permission levels and artifact states. This feedback loop enables automatic propagation while managing complexity through intelligent decision-making rather than rigid rules
Solution Approach 2:
The system dynamically changes propagation parameters such as propagation depth, artifact selection criteria, and permission thresholds based on the specific context of each propagation task. This allows the system to adapt to different scenarios without requiring complex manual configuration
3Stability of the object's composition
If extensions are propagated to all related artifacts, then consistency across the data model is improved, but the risk of conflicts and errors increases
Solution Approach 1:
The system applies different propagation strategies to different types of artifacts based on their specific characteristics, relationships, and permission levels. Rather than treating all artifacts uniformly, it evaluates each target artifact individually to determine the appropriate propagation approach, thereby maintaining consistency while minimizing conflicts
4Manufacturing precision
If manual verification of each extension propagation is performed, then accuracy and conflict prevention are improved, but the process becomes more tedious and time-consuming
Solution Approach 1:
The system performs self-verification of extension propagations by automatically checking compatibility, permissions, and potential conflicts before and during the propagation process. This self-service capability maintains high accuracy while eliminating the need for manual verification of each propagation step
Data Source
AI summary
Techniques and solutions are described for propagating extensions to data artifacts, such as data artifacts defining objects in a physical or virtual data model. One or more data artifacts are identified that are related to a first data artifact. One or more extension elements of the first data artifact are analyzed for propagation to at least one data artifact of the one or more data artifacts. Analyzing whether an extension element should be propagated can include analyzing a type of the extension element, a type of operation or context in which the extension element is used, or how the at least one data artifact refers to, uses, or incorporates the first data artifact, including particular elements thereof. The results of the analysis are compared with various rules. Extension elements are propagated automatically, manually upon user approval (e.g., propagation recommendations are provided), or in a semi-automated manner.