Proxy Server Data Synchronization for Dissimilar Schema Compatibility
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing automated synchronization methods for address books are limited to data sources with the same data schema, making it challenging to synchronize data between sources with dissimilar schemas.
Innovation Solution
A system utilizing a proxy server to identify corresponding and inconsistent data entries across data tables with different schemas, generating dissimilarity indicators, and determining priority to synchronize data by modifying entries in both tables, ensuring data consistency across disparate data sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated synchronization methods are used, then synchronization efficiency is improved, but data schema compatibility is limited
Solution Approach 1:
The patent introduces a proxy server as an intermediary component between data sources with different schemas. The proxy server receives data from multiple data sources, normalizes the data according to a common schema, and then distributes the normalized data to other data sources. This intermediary approach enables automated synchronization between dissimilar data sources without requiring direct compatibility between them.
Solution Approach 2:
The patent transforms data entries by changing their parameters (data types, formats, and structures) to match a common target schema. The system identifies corresponding fields between source and target schemas, converts data types (e.g., converting phone numbers from different formats), and adjusts field structures to enable synchronization between data sources with different original schemas.
2Adaptability or versatility
If data normalization is performed to handle dissimilar schemas, then schema compatibility is improved, but processing complexity increases
Solution Approach 1:
The patent segments the data normalization process into distinct stages: (1) receiving data from multiple data sources, (2) identifying corresponding fields between source and target schemas, (3) converting data types and formats, and (4) distributing normalized data. This segmentation allows the complex normalization task to be broken down into manageable steps that can be processed systematically by the proxy server.
Solution Approach 2:
The proxy server is designed as a universal component that can handle multiple data sources with different schemas and normalize them to a common schema. The system maintains a library of schema information and conversion rules that enable it to process various data types and formats, making the normalization process more manageable through standardized procedures.
3Reliability
If manual updates are performed to synchronize address books, then data accuracy is maintained, but time consumption increases
Solution Approach 1:
The system implements automated self-service synchronization where the proxy server automatically detects changes in data sources, identifies corresponding fields, normalizes the data, and updates other data sources without human intervention. This eliminates the need for manual updates while maintaining data accuracy through systematic automated processing.
Solution Approach 2:
The patent implements feedback mechanisms where the proxy server monitors changes in data sources, compares updated data with existing data, and automatically propagates changes to other data sources. The system uses schema information to track which fields have changed and ensures that only relevant updates are applied, maintaining accuracy while reducing time consumption.
Data Source
AI summary
A method is provided for synchronizing data sources. The method includes receiving at least first and second data tables. The data tables have one or more mutually similar fields and one or more dissimilar fields from one another. First normalized, second normalized, and intermediate data tables are stored, each including respective first normalized, second normalized, and intermediate data table fields that each correspond to the mutually similar fields of the first and second data tables. The first normalized data table is at least partially populated with corresponding entries from the first data table and the second normalized data table is at least partially populated with corresponding entries in the second data table. Intermediate data table entries are respectively replaced with corresponding inconsistent data entries of the first and second normalized data tables. An apparatus and a computer program product for accomplishing the above method are also provided.