Configurable Computer Platform for Metadata-Driven Data Processing
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Solution Overview
Problem
Current computer systems face challenges in efficiently maintaining and modifying their architecture and software to adapt to changing data communication methods and external data sources, leading to high maintenance and programming costs.
Innovation Solution
A configurable computer platform is developed, allowing processes to be broken down into functional units with metadata-driven design, enabling configuration-driven data processing and reducing the need for extensive programming and maintenance through a unified data processing framework that supports various data sources and formats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If computer systems are reconfigured to adapt to changing data communication methods and external data sources, then adaptability is improved, but maintenance cost and programming effort increase
Solution Approach 1:
The patent implements a universal data processing framework that can handle multiple data sources, communication methods, and data formats through a single unified architecture. This framework provides common data access interfaces, standardized processing pipelines, and configurable connectors that work across different external systems, eliminating the need to develop and maintain separate integration code for each data source.
Solution Approach 2:
The system divides data processing into modular functional components including data access layer, validation layer, processing layer, and output layer. Each layer is independently configurable and can be modified without affecting others, allowing targeted updates to specific data sources or processing rules while maintaining overall system stability and reducing maintenance scope.
2Adaptability or versatility
If computer architecture is modified to meet new computing requirements, then functionality is improved, but design and testing cost increase
Solution Approach 1:
The patent implements a dynamic configuration system where processing logic, data sources, and business rules can be modified at runtime without requiring system redesign. Configuration parameters, data source connections, and processing rules are stored in configurable repositories that can be updated dynamically, allowing the system to adapt to new requirements through configuration changes rather than architectural redesign.
Solution Approach 2:
The framework introduces intermediary abstraction layers between the core processing engine and external data sources. These intermediaries include standardized connectors, adapters, and interface layers that isolate the core system from external changes, allowing new data sources to be integrated through intermediary components rather than modifying the core architecture.
3Adaptability or versatility
If programming is done from scratch for each computer task, then customization is improved, but time expenditure and resource consumption increase
Solution Approach 1:
The patent implements pre-configured processing templates, standardized data access patterns, and reusable processing pipelines that can be applied to common data processing scenarios. These pre-built components include validated processing logic, error handling routines, and integration patterns that can be configured for specific tasks without requiring development from scratch, significantly reducing programming time while maintaining customization capability.
Solution Approach 2:
The system enables replication of successful processing configurations across multiple tasks and data sources. Once a processing pipeline is configured and validated for one data source, it can be copied and adapted for other similar data sources, reducing the need to reprogram common processing logic and accelerating deployment of new data processing tasks.
Data Source
AI summary
Computer processes are provided which can be executed without business or commercial context, independent of the kind of data or other content associated with the computer processes. In one embodiment, a computer process can be broken down into functional units, and the metadata associated with the functional units can be extracted. Each functional unit can then be represented by an interface and also coded with computer-readable instructions to use one or more configuration sets which have been defined by the metadata. The computer process can then be implemented by programming the functional units to execute based on a configuration set determined by predefined operating parameters.