Universal Data Transformation Engine for Multi-Source Integration
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Solution Overview
Problem
Current computer systems require separate information gathering applications for each external application, leading to inefficiencies in capturing and processing user interactions from diverse sources like social media and portals, which are not easily adaptable to new or future activities.
Innovation Solution
A qualifying system that receives channel activity records from various external systems, applies user-configurable qualification and conversion rules to transform these records into target entities within the computing system, allowing for synchronous or asynchronous data transformation and enabling the creation of multiple target entities from a single channel activity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If separate information gathering applications are developed for each external application, then the system can capture user interactions from diverse sources, but the device complexity and development time increase significantly
Solution Approach 1:
The patent implements a universal information gathering application that can handle multiple external applications through configurable rules and parameters. Instead of creating separate applications for each external system, a single application uses rule-based configuration to adapt to different data sources, formats, and transformation requirements, thereby reducing overall system complexity while maintaining versatility
Solution Approach 2:
The system uses configurable rules and parameters to adapt its behavior based on the specific external application being integrated. By changing parameters such as data source connections, transformation rules, and target entity mappings, the same information gathering application can serve multiple purposes without requiring separate codebases for each integration scenario
2Reliability
If custom information gathering applications are developed for each external system, then specific data capture requirements are met, but the ease of operation and maintenance decrease
Solution Approach 1:
A single information gathering application provides universal functionality across multiple external systems through configurable rules. This eliminates the need to operate and maintain multiple separate applications, while still achieving reliable data capture for each specific external system through parameter configuration rather than custom code development
3Adaptability or versatility
If the system is designed to be highly adaptable to new external applications, then future extensibility is improved, but the initial device complexity increases
Solution Approach 1:
The system architecture is segmented into distinct configurable components: connection parameters, qualification rules, conversion rules, and target entity mappings. This modular rule-based structure allows new external applications to be integrated by configuring individual rule segments rather than redesigning the entire system, thereby improving extensibility without proportionally increasing overall complexity
Data Source
AI summary
A qualifying system receives a channel activity record from one of a plurality of different external systems, over one of a plurality of different communication channels. It accesses qualification rules to determine whether the channel activity record is to be transformed into one or more target entities in a computing system. If so, a conversion engine accesses user-configurable mappings and conversion rules to identify conversion actions that are to be taken in order to transform the channel activity record into one or more target entities. The conversion engine performs a data transformation on the channel activity record to transform it into the identified one or more target entities.