Data Integration Mapping for Common Interface Adaptability
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Solution Overview
Problem
Existing data management systems face high costs and inefficiencies when integrating with other systems due to the need for redesigning interfaces upon changes, leading to poor versatility in data interaction.
Innovation Solution
A configuration method that maps the data structure of a data source with an external object using access credentials, enabling data communication through a common data interface without requiring specific interface redesign, thus reducing management and maintenance costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If interactive interfaces are agreed in advance between data management system and other systems, then data interaction can be performed through network communication, but the versatility is poor and high costs are incurred when other systems need to be changed
Solution Approach 1:
The patent implements a universal data interaction interface that can adapt to multiple different data sources and systems. The interface uses a standardized protocol structure that can handle various data types and sources without requiring system-specific customizations, thereby achieving multi-functionality and versatility while maintaining stable data interaction.
Solution Approach 2:
The patent employs parameter-based configuration to adapt the data interaction interface to different systems. By changing parameters such as data source identifiers, query templates, and mapping relationships, the same interface can work with different systems without structural modifications, thus improving versatility while maintaining reliability.
2Adaptability or versatility
If interactive interfaces are redesigned and developed for each system change, then data interaction can be customized, but the cost of virtual integration increases
Solution Approach 1:
The patent creates a universal interface framework that can be configured for different systems through parameter settings rather than requiring actual redesign and development. This framework handles various data sources, authentication methods, and query types, eliminating the need for costly custom development while maintaining customization capability.
Solution Approach 2:
The patent uses template-based configuration where standardized interface patterns are copied and adapted for different systems. Instead of developing unique interfaces from scratch, the system replicates and configures proven interface templates, significantly reducing development costs while maintaining adaptability to different data sources.
3Productivity
If specific interface design is implemented for each data source, then data access can be optimized, but data management and maintenance costs increase
Solution Approach 1:
The patent implements a universal data access interface that maintains high efficiency across different data sources through standardized query templates and optimization strategies. The interface handles authentication, data retrieval, and result processing in a unified manner, reducing management complexity while preserving data access efficiency through configurable parameters.
Solution Approach 2:
The patent merges multiple interface design patterns into a single unified framework that combines the strengths of different approaches. By consolidating authentication mechanisms, query processing, and data transformation into one standardized interface, the system achieves efficient data access without the overhead of managing multiple separate interface designs.
Data Source
AI summary
The disclosure provides a configuration method, data integration method, apparatus, device and storage medium of data integration strategy. The method includes obtaining a data structure of a data source based on an access credential of the data source; and configuring a data structure of an external object for the data structure of the data source, wherein there is a mapping relationship between the data structure of the external object and the data structure of the data source.