Process Cloud Services Integration with Intelligence Cloud via Data Conversion
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Solution Overview
Problem
Process Cloud Services (PCS) lack the capability to fully utilize and analyze analytics data outside of its environment, limiting its functionality and user benefits.
Innovation Solution
Integration of PCS with Intelligence Cloud Service (ICS) through the use of PCS analytics data export APIs, semantic models, and ICS integration services, allowing for data conversion, distribution, and utilization by external business intelligence systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If PCS analytics data is kept within the PCS environment, then data security and system simplicity are maintained, but data analysis capabilities and user benefits are limited
Solution Approach 1:
The patent introduces an intermediary component that bridges PCS and external business intelligence systems. This intermediary enables data transfer and analysis capabilities while maintaining system boundaries and security, thus improving adaptability without proportionally increasing complexity.
Solution Approach 2:
The system is segmented into distinct components: the core PCS environment, the integration layer, and external analytics systems. This segmentation allows each component to maintain its own complexity level while enabling collaborative data analysis across boundaries.
2Adaptability or versatility
If PCS integrates with external intelligence cloud services, then data analysis and user capabilities are enhanced, but integration complexity and data transfer overhead increase
Solution Approach 1:
The integration mechanism is designed with universal interfaces that can work with multiple external intelligence cloud services. This multi-functionality approach allows a single integration framework to support various analytics platforms, enhancing user capability while avoiding the need for separate integration solutions for each service.
Solution Approach 2:
An intermediary integration layer is introduced that handles the complexity of external service connections. This mediator manages data transfer protocols, authentication, and compatibility issues, thereby enhancing user capability while containing integration complexity within a dedicated component rather than propagating it throughout the entire system.
3Ease of operation
If PCS data is exported and converted for external systems, then data usability in external systems is improved, but data processing time and conversion overhead increase
Solution Approach 1:
The system performs preliminary data preparation and conversion operations in advance, before external systems request the data. This includes pre-formatting data according to common external system requirements and pre-establishing connection protocols, thereby reducing the time required for actual data export and conversion when needed.
Solution Approach 2:
The integration mechanism dynamically adjusts data format parameters based on the target external system's requirements. By changing parameters such as data structure, encoding, and protocol type only when and where needed, the system improves data usability for specific external systems while minimizing unnecessary conversion overhead for data that doesn't require transformation.
Data Source
AI summary
A process cloud services (PCS) system is integrated with an intelligence cloud service (ICS) based on converted PCS analytics data. The PCS system converts PCS analytics data into a format for the ICS resulting on converted PCS analytics data. The converted PCS analytics data is transferred from the PCS system to the ICS. The PCS system is integrated with the ICS based on the converted PCS analytics data received at the ICS.