Negotiated Schema for Multi-Source Data Integration
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Solution Overview
Problem
Interacting with data sources having different data storage schemas is tedious and time-consuming, as end users or computing systems must navigate and understand each data structure independently, making it difficult to access similar data types stored in varying structures.
Innovation Solution
The system generates a negotiated schema by determining and comparing the schemas of multiple data sources, interrelating corresponding data points, and storing the negotiated schema, allowing for querying across multiple data sources without requiring individual querying of each source.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If multiple data sources with different data storage schemas are accessed independently, then data retrieval completeness is improved, but operation complexity and time consumption increase significantly
Solution Approach 1:
The patent merges multiple data sources with different schemas into a unified virtualized data structure. This unified structure allows queries to access data from multiple sources simultaneously through a single interface, combining the benefits of complete data retrieval while eliminating the complexity of independent access to each data source.
Solution Approach 2:
The patent introduces a mediator component that translates between different data storage schemas and a unified virtualized structure. This intermediary layer handles schema differences, data mapping, and query translation, allowing users to query multiple data sources without needing to understand or navigate their individual schemas.
2Loss of information
If each data source is queried independently to ensure complete data retrieval, then information availability is improved, but time consumption increases
Solution Approach 1:
The patent performs preliminary actions by pre-establishing the unified virtualized data structure that incorporates schemas from multiple data sources. This structure is built in advance, allowing queries to be executed against the unified structure rather than requiring sequential independent queries of each data source, significantly reducing time consumption while maintaining complete information availability.
3Reliability
If disparate data structures are navigated independently, then understanding of each data structure is improved, but system complexity increases
Solution Approach 1:
The patent creates a universal virtualized data structure that can represent and access data from multiple different data storage schemas through a single unified interface. This multi-functional structure eliminates the need for users to understand or navigate multiple disparate data structures, reducing system complexity while maintaining the ability to access and understand data from each source through the unified framework.
Data Source
AI summary
Systems and methods generating schemas that represent multiple data sources are provided herein. According to some embodiments, methods may include determining a schema for each of the multiple data sources via a computing device communicatively couplable with each of the multiple data sources, each of the multiple data sources including one or more data structures that define how data is stored in the data source, generating a negotiated schema by comparing the schemas of the multiple data sources to one another and interrelating data points of the multiple data sources based upon the schemas, interrelating the negotiated schema with the schema for each of the multiple data sources based upon the interrelation of the data points, and storing the negotiated schema in a storage media by way of the computing device.