License Data Mapping System for Disparate Professional Records
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Solution Overview
Problem
Professional records from disparate data sources and databases have varying structures and formats, making it difficult to access and process them accurately and efficiently, and there is a need for an automated system to map licenses data and track changes, update queries, and provide status information.
Innovation Solution
A system and method for mapping licenses from disparate data sources, involving data structure analysis, cross-referencing license records with third-party information, flagging changes, and updating procedures, while allowing end-users to edit records and report violations, using an Interactive Directory of Professionals (IDP) system that integrates with third-party databases and verification systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual processing of professional records from disparate data sources is used, then data accuracy can be maintained through human verification, but processing efficiency and productivity are severely reduced
Solution Approach 1:
The patent introduces an automated mapping system that acts as an intermediary between disparate data sources and the target database. This system uses data structure analysis, cross-referencing, and automated flagging mechanisms to maintain data accuracy while dramatically improving processing efficiency. The intermediary automatically handles the complex task of mapping licenses data from multiple sources with varying structures and formats.
Solution Approach 2:
The patent replaces manual mechanical processing with automated computational systems. The automated mapping system, data structure analysis tools, and cross-referencing algorithms substitute human operators, enabling high-volume processing of professional records while maintaining consistency and accuracy through systematic automated procedures.
2Productivity
If automated mapping systems are implemented to improve processing efficiency, then productivity increases, but system complexity and difficulty of detecting and measuring data relationships increase
Solution Approach 1:
The patent segments the automated mapping system into distinct functional modules: data structure analysis component, cross-referencing component, automated flagging component, and update procedure component. Each module handles a specific aspect of the mapping process, making the overall complex system more manageable, maintainable, and easier to debug while preserving high processing efficiency.
Solution Approach 2:
The patent creates a universal mapping system that can handle multiple data sources with varying structures and formats through a single integrated platform. The system uses standardized data structures and flexible cross-referencing capabilities to accommodate different professional record formats, reducing the need for multiple specialized systems.
3Speed
If automated mapping systems are used to process licenses data efficiently, then processing speed improves, but reliability and accuracy of mapping relationships may deteriorate due to automated errors
Solution Approach 1:
The patent implements feedback mechanisms where the automated mapping system continuously monitors and adjusts its mapping relationships based on cross-referencing results and flagged changes. The system provides feedback loops that verify mapping accuracy, allow for correction of automated errors, and improve reliability while maintaining high processing speeds through optimized algorithms.
Solution Approach 2:
The patent performs preliminary data structure analysis and validation before the actual mapping process. By pre-processing and validating data structures, cross-referencing schemas, and mapping rules in advance, the system reduces the likelihood of automated errors during high-speed processing, thereby maintaining both speed and reliability.
4Reliability
If comprehensive tracking of license field changes is implemented to improve data reliability, then data quality improves, but loss of time and processing overhead increase
Solution Approach 1:
The patent implements periodic automated flagging and tracking of license field changes rather than continuous monitoring. The system periodically scans for changes, updates mapping relationships, and refreshes data quality metrics at scheduled intervals, maintaining high data reliability while minimizing processing overhead and time loss compared to continuous real-time monitoring.
Data Source
AI summary
A system and method for mapping licenses from disparate data sources and databases from third parties triggered by a system registration request, analyzing data structures for license information records and third-party information records, cross-referencing a license record with a third-party information record, flagging database records that reflect a license field record change, updating mapping-related procedures and queries, and providing a presentation of license information records and related status.