Domain Event Stream for Real-Time Cross-Platform Analytics
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Solution Overview
Problem
Conventional analytics systems face inefficiencies in communicating and adapting to cross-system changes and actions due to delayed and fragmented communications, leading to redundant resource utilization and inflexibility in interacting with diverse computing systems.
Innovation Solution
The implementation of a digital analytics system that relays domain-event objects within an enhanced multi-platform data stream to listen for and react to digital events across various computing platforms in real or near-real time, using domain-event objects and listener rules to perform platform actions dynamically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If conventional analytics systems use scheduled data requests to collect information from other computing systems, then they can maintain data updates, but the reactions to changes are delayed and not real-time
Solution Approach 1:
The patent replaces periodic scheduled data requests with event-driven periodic actions. Domain events are published immediately when changes occur in source systems, and domain event listeners continuously monitor and react to these events in real-time, eliminating the delay inherent in scheduled periodic requests while maintaining systematic data update mechanisms
Solution Approach 2:
The patent implements feedback mechanisms where domain event listeners continuously monitor the data stream for changes and immediately trigger reactions. This closed-loop feedback system ensures that data changes are detected and acted upon in real-time, rather than waiting for the next scheduled request cycle
2Productivity
If conventional analytics systems use separate data request calls for each computing system, then they can collect data from multiple sources, but computing resources are inefficiently utilized due to redundancies
Solution Approach 1:
The patent merges multiple separate data request calls into a single unified domain event stream. Instead of making individual requests to each computing system, the system consolidates data changes from multiple sources into one standardized event stream that all domain event listeners can consume, eliminating redundant requests and optimizing resource utilization
Solution Approach 2:
The patent creates a universal domain event stream that serves multiple functions: it consolidates data from diverse computing systems, provides a standardized interface for all domain event listeners, and enables simultaneous consumption by multiple systems. This single multi-functional mechanism replaces numerous specialized data request calls
3Adaptability or versatility
If conventional analytics systems rigidly determine which computing systems to send information to using complex protocols, then they can manage communications, but the systems cannot easily communicate with a wide variety of other computing systems
Solution Approach 1:
The patent introduces a domain event stream as an intermediary layer between diverse computing systems and domain event listeners. This standardized intermediate format translates and normalizes data from various source systems, allowing the analytics system to communicate with diverse platforms without managing complex individual API configurations for each system
Solution Approach 2:
The patent creates a universal domain event stream format that can accommodate data from multiple different computing systems and protocols. This single standardized interface provides multi-functionality, enabling the system to communicate with diverse platforms through one unified mechanism rather than requiring separate configurations for each system
4Productivity
If conventional analytics systems make sequential data request calls to identify changes, then they can systematically check for updates, but the process is fragmented and delayed rather than simultaneous
Solution Approach 1:
The patent implements continuous monitoring of the domain event stream by domain event listeners, replacing fragmented sequential requests with an unbroken continuous stream of event detection and reaction. This continuous action ensures that data changes are identified and reacted to immediately as they occur, without the gaps and delays inherent in sequential periodic requests
Data Source
AI summary
This disclosure relates to methods, non-transitory computer readable media, and systems that relay domain-event objects within an enhanced multi-platform data stream to listen for and react to digital events indicated by the domain-event objects that occur across a wide variety of computing platforms. Specifically, the disclosed systems can receive domain-event objects within the multi-platform data stream. From among the domain-even objects transmitted through the multi-platform data stream, the disclosed systems can identify a domain-event object that is relevant to a digital-analytics platform by identifying domain-event objects that include properties satisfying domain-event-listener rules. Based on an entity identifier and an object event from the relevant domain-event object, the disclosed systems can perform a platform action within the digital-analytics platform (e.g., to react to a change in another platform as indicated by the domain-event object).