In-Memory Policy Analytics Architecture for Real-Time Scenario Analysis
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Solution Overview
Problem
Current systems lack efficient mechanisms for quickly and accurately analyzing policy scenarios and their outcomes in real-time, especially in large data sets, which is crucial for business and academic computing.
Innovation Solution
A method and system for in-memory policy analytics that creates policy models to represent scenarios, allowing for real-time analysis and visualization of policy outcomes, using a policy analytics architecture that includes a policy modeling application, policy automation hub, input databases, analysis databases, and an analysis server for rapid data processing and scenario execution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If traditional data processing methods are used for policy scenario analysis, then system complexity is reduced, but analysis speed and real-time capability deteriorate
Solution Approach 1:
The patent replaces traditional mechanical data processing systems with an in-memory computing system that uses volatile memory (RAM) to store and process policy data, scenario definitions, and analysis results. This substitution enables real-time analysis by eliminating disk I/O bottlenecks and enabling direct memory access, thereby achieving high-speed policy scenario analysis while managing complexity through specialized hardware-software integration.
Solution Approach 2:
The patent changes the fundamental parameter of data storage location from persistent storage (disks) to volatile memory (RAM). This parameter change enables dramatically faster data access speeds (nanoseconds vs. milliseconds), allowing real-time policy analysis. The system dynamically loads policy data, scenario configurations, and analysis results into memory, enabling rapid what-if analysis and scenario comparison without traditional storage latency.
2Loss of time
If real-time policy analysis is implemented, then responsiveness to policy changes is improved, but processing time requirements worsen
Solution Approach 1:
The patent performs preliminary actions by pre-loading policy data, scenario definitions, and analysis configurations into volatile memory before actual analysis is needed. The system pre-compiles policy rules, pre-validates scenario parameters, and pre-structures data relationships in memory, so that when analysis is triggered, the system can immediately execute without data loading delays. This preliminary preparation enables real-time responsiveness while maintaining high throughput.
Solution Approach 2:
The patent maintains continuous useful action by keeping policy data and analysis results resident in volatile memory during analysis operations. The in-memory architecture eliminates idle time between data retrieval and processing, allowing continuous computation on policy scenarios. The system continuously maintains policy models, scenario definitions, and analysis results in an accessible state, enabling uninterrupted real-time analysis and rapid iteration through multiple what-if scenarios.
Data Source
AI summary
A method, system, and computer-program product for in-memory policy analytics are disclosed. The method includes creating a policy model and determining an effect of a change to one of a value of one of one or more parameters. The policy model is configured to represent one or more policy scenarios by virtue of comprising one or more parameters, and each of the one or more scenarios is defined, at least in part, by each of the one or more parameters comprising a value or a plurality of values. Further, the effect is on at least one of the one or more scenarios.