Digital Records for Multi-Application Network State Transitions
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Solution Overview
Problem
In multi-application networks, there is a need to efficiently monitor, track, and analyze computing operations and data to facilitate legacy optimization, efficient data management, and exception event handling, while minimizing time constraints and navigating multiple user interfaces.
Innovation Solution
A method and system that generate digital records indicating computing operations and state data transitions for digital request data objects, using context data including user profiles, trajectory data, and metadata, with a digital assistant executing computing operations and updating context data to recommend analysis operations and resolve exception events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If multiple user interfaces are used to monitor and manage computing operations, then comprehensive data access is achieved, but user cognitive load and training time increase
Solution Approach 1:
The patent consolidates multiple user interfaces into a single unified interface that displays digital records containing computing operation data, state data, and context information. This merging approach maintains comprehensive data access while reducing the cognitive load of navigating multiple interfaces and the training time required to master them.
2Measurement precision
If manual monitoring and tracking of computing operations is performed, then detailed analysis is possible, but time consumption increases
Solution Approach 1:
The system automatically generates digital records that capture computing operation data, state data, and context information without requiring manual intervention. The digital assistant component autonomously monitors, tracks, and analyzes operations, providing detailed information while eliminating the time consumption associated with manual processes.
Solution Approach 2:
The system pre-generates and maintains digital records with comprehensive operation data and context information before user analysis is needed. This preliminary capture and organization of data enables rapid, detailed analysis when users query the system, avoiding time-consuming manual collection and processing.
3Reliability
If context data is updated after each computing operation, then data accuracy is maintained, but processing overhead increases
Solution Approach 1:
The system continuously updates context data and generates digital records in an ongoing manner as computing operations occur, rather than performing batch updates. This continuous process maintains data accuracy by capturing state changes immediately while distributing processing overhead over time, avoiding large concentrated processing loads.
Data Source
AI summary
The disclosed methods include: determining context data for a digital request data object based on a received first input; executing, based on the context data and the first input: a first and a second computing operation; generating a first digital record indicating: summary data for the first and second computing operations, and first state data associated with transitioning the digital request data object from a first data state to a second data state; updating context data based on the first digital record; executing, based on the updated context data and/or a received second input: a third and a fourth computing operation; generating a second digital record indicating: summary data for the third and the fourth computing operations, and second state data associated with transitioning the digital request data object from: the second data state to a third data state, and from the third data state to a fourth data state.