Tagged Database Rule Management for Faster Related-Structure Updates
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Solution Overview
Problem
Existing data processing networks face challenges in efficiently managing and modifying large numbers of data structures, leading to delays and sub-optimal resource usage due to manual intervention, inefficient storage, and lack of automated rule management.
Innovation Solution
A rules management (RM) computing device that retrieves, tags, and parses rules in a database to identify related rules, allowing for automated modification and display of suggested changes, enhancing efficiency and reducing manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If manual modification of data structures is used, then changes can be implemented with simple tools, but the implementation delay increases substantially
Solution Approach 1:
The system enables self-service automation where the database management system automatically identifies, retrieves, and modifies related data structures based on template rules without requiring manual intervention for each individual structure, thus reducing implementation delay while maintaining ease of modification
Solution Approach 2:
The system performs preliminary actions by pre-defining template rules and automatically identifying all related data structures before modification is needed, so that when a change is required, the system can quickly apply the modification to all identified structures simultaneously rather than manually searching for and modifying each one
2Device complexity
If manual modification of data structures is used, then resource usage is simpler to manage, but sub-optimal usage of database storage and computing power occurs
Solution Approach 1:
The system implements feedback mechanisms where the database management system continuously monitors and analyzes the data structure repository, automatically identifying relationships between structures and providing feedback on optimization opportunities, thereby improving resource utilization without significantly increasing management complexity
Solution Approach 2:
The system transitions from static manual management to dynamic automated management where the database management system actively and continuously optimizes data structure storage and computing resource allocation based on real-time analysis, improving productivity while keeping management complexity manageable through automation
3Adaptability or versatility
If the number of data structures increases, then the system can handle more complex data processing tasks, but the complexity of modifying and tracking data structures increases
Solution Approach 1:
The system applies segmentation by organizing data structures into hierarchical groups and categories within the repository, allowing the database management system to efficiently locate, retrieve, and modify specific structures or groups of structures without being overwhelmed by the total number of data structures in the system
Solution Approach 2:
The database management system acts as an intermediary between users and the large number of data structures, automatically identifying relationships, retrieving relevant structures, and coordinating modifications across multiple structures, thereby reducing the complexity of modification and tracking while maintaining high adaptability
Data Source
AI summary
A computing device may be provided. The computing device may include at least one processor configured to retrieve, from a database, a plurality of data structures, each of the plurality of data structures including one or more data elements that generate an output value based on an input value, generate, for each of the plurality of data structures, one or more tags based on the one or more data elements, store the generated tags in the database in association with the plurality of data structures, receive, from a first user computing device, a proposed modification for a target data structure of the plurality of data structures, parse the database to identify related data structures based on the one or more tags associated with the target data structure, and cause to be displayed, on the first user computing device the identified related data structures.