Event Broker for Cross-Platform Business Process Monitoring
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Solution Overview
Problem
Business process monitoring in data processing systems is challenging due to disparate data processing platforms with unique data formats, making it difficult to provide real-time, up-to-date progress reports to business users.
Innovation Solution
A method and system that receive event data from multiple platforms, derive address information, map it to process status indicators, and display these indicators to users, enabling integration of data across platforms and providing current business process reports.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is collected from multiple disparate data processing platforms with unique data formats, then comprehensive business process monitoring capability is improved, but system complexity and difficulty of integration increase
Solution Approach 1:
The patent introduces an event broker as an intermediary component that receives events from multiple disparate data processing platforms and distributes them to appropriate subscribers. This mediator layer abstracts the complexity of integrating different platforms with unique data formats, allowing the system to maintain comprehensive monitoring capability without directly managing the complexity of each platform's data structure. The event broker standardizes event routing and data distribution across the heterogeneous system.
Solution Approach 2:
The patent implements a universal event schema and subscription mechanism that can handle events from any data processing platform. The system uses a standardized event structure with common fields (event type, timestamp, source system, data) that can accommodate events from diverse sources. This universal approach allows the monitoring system to work with multiple platforms simultaneously without requiring platform-specific integration logic for each subscriber.
2Measurement precision
If real-time event data is collected and processed from all platforms, then monitoring accuracy and up-to-date information are improved, but data processing time and computational resources increase
Solution Approach 1:
The patent implements event filtering and selective subscription mechanisms where subscribers only receive and process events relevant to their specific monitoring needs. Rather than processing all events from all platforms, each subscriber can filter events based on event type, source system, or other criteria. This partial processing approach maintains monitoring accuracy for relevant events while significantly reducing the overall data processing burden and computational resources required.
Solution Approach 2:
The system performs preliminary event validation, categorization, and routing at the event broker level before events reach subscribers. Events are pre-processed to extract key attributes and determine appropriate routing destinations. This preliminary action reduces the processing burden on individual subscribers, allowing them to focus only on their specific monitoring requirements without having to parse and filter raw events from multiple platforms.
3Reliability
If proprietary data formats from each platform are maintained, then platform-specific data integrity is preserved, but interoperability and ease of operation decrease
Solution Approach 1:
The patent implements a dual-format approach where events maintain their original platform-specific data structure and format locally, while simultaneously providing a standardized view for cross-platform processing. The event broker preserves the proprietary data formats from each source platform in the original event payload, ensuring data integrity and platform-specific requirements are met. At the same time, the system extracts and standardizes key event attributes into a common schema for interoperability. This allows each platform's data to retain its local quality and integrity while enabling seamless integration and operation across the entire system.
Data Source
AI summary
A method of monitoring a data processing system which is processing a transaction, comprising steps of: receiving event data from each of a plurality of data processing sub-systems making up the data processing system, the event data corresponding to events taking place within the plurality of data processing sub-systems as the data processing system processes the transaction; deriving address information from the event data; mapping the address information to corresponding process status indicator labels; and displaying the process status indicator labels for review by a user.


