Service-Oriented Data Transformation Registry
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Solution Overview
Problem
Current data integration systems face challenges in efficiently managing and integrating data across disparate applications within a business enterprise, leading to inefficiencies such as repetitive data entry and failure to capitalize on data that could benefit other processes, due to the complexity of existing enterprise application integration solutions.
Innovation Solution
A transformation function of the extract-transform-load data integration process is deployed as a service in a services-oriented architecture, providing a module for data integration functions like data transformation, metadata management, and data quality, which can be accessed through a registry and interface, facilitating integration across various platforms and formats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional enterprise application integration solutions are used, then data can be integrated across applications, but the system complexity and development time increase significantly
Solution Approach 1:
The patent segments the data integration system into independent, reusable service components including extraction services, transformation services, and loading services. Each service is encapsulated as a separate deployable unit that can be independently developed, maintained, and reused across multiple integration scenarios, thereby reducing overall system complexity while maintaining integration capability.
Solution Approach 2:
The patent creates universal service templates and reusable transformation functions that can be applied across different data integration scenarios. These services are designed to handle multiple data types and integration patterns through configuration rather than custom coding, enabling the same service infrastructure to serve diverse integration needs without increasing complexity.
2Adaptability or versatility
If custom integration solutions are developed for each application, then specific integration requirements are met, but development time and code redundancy increase
Solution Approach 1:
The patent pre-defines service templates, transformation functions, and integration patterns that can be directly applied to common integration scenarios. By preparing these reusable components in advance, the system eliminates the need to develop custom integration logic from scratch for each new application, significantly reducing development time while maintaining the ability to customize through configuration.
Solution Approach 2:
The patent enables replication of proven integration services and transformation functions across multiple integration projects. Once a service is developed and validated for one integration scenario, it can be copied and reused for similar scenarios with minimal modification, eliminating redundant development effort and accelerating deployment.
3Reliability
If data integration functions are hard-coded in each application, then integration logic is embedded, but maintenance difficulty and code duplication increase
Solution Approach 1:
The patent extracts integration logic from individual application codebases and places it into separate, dedicated service components. This separation allows integration logic to be maintained, updated, and repaired independently of the applications that consume it, significantly improving maintainability while preserving the stability and reliability of the integration functionality.
4Productivity
If comprehensive data integration is implemented, then data synchronization improves, but system resource consumption increases
Solution Approach 1:
The patent implements incremental data synchronization and change data capture mechanisms that process only the necessary portion of data rather than complete data sets. By applying partial action principles, the system achieves effective data synchronization across distributed applications while minimizing the computational resources required for data movement and transformation.
Data Source
AI summary
A transformation function of an extract-transform-load data integration process is deployed as a service in a services oriented architecture. A method includes providing a module for a data integration function, the module being a data transformation module; providing a registry of services; providing an interface for the data transformation module; and identifying the data transformation module in the registry; wherein the data transformation module can be accessed as a service in a services oriented architecture. A system includes a data transformation module for a data integration function; a registry of services; and an interface for the data transformation module; wherein the data transformation module is identified in the registry; and wherein the data transformation module can be accessed as a service in a services oriented architecture.