Data Migration Validation via Entity-Level Comparison
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Solution Overview
Problem
Existing data migration processes often result in data loss or corruption during the transfer from one system to another, with current validation methods only providing a count of corrupt items, which is insufficient for ensuring individual user data integrity.
Innovation Solution
A method and system that migrate entity data from a first data store to a second using different data protocols for validation, comparing data sets from both stores to identify discrepancies and validate the migration at a user or entity level, allowing for user-level release of data and refinement of migration errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is migrated using a standardized file format transformation process, then data can be transferred between systems, but data loss or corruption may occur during the transformation and transmission process
Solution Approach 1:
The patent implements a feedback mechanism by querying both the source and destination data stores with identical queries and comparing the result sets. This comparison process provides feedback on whether data migration was successful, identifying any discrepancies between the source and migrated data, and enabling validation of data integrity at the individual entity level.
2Measurement precision
If a corrupt item count validation method is used, then service-level data loss can be detected, but individual user data migration status cannot be determined
Solution Approach 1:
The patent segments the validation process from the migration process. While migration transforms and transfers data using standardized formats, validation separately queries both data stores using the same protocol and compares results. This segmentation allows individual entity-level validation without interfering with the migration workflow, providing detailed user-specific migration status information.
Solution Approach 2:
The patent introduces an intermediary validation process that uses a common data protocol to query both the source and destination data stores. This intermediary approach compares the query result sets to identify discrepancies, serving as a mediator that validates individual user data migration status without being part of the original migration transformation process.
3Adaptability or versatility
If data is transformed into a standardized file format and then into a native format for the second system, then data can be migrated between different systems, but opportunities for data corruption increase at each transformation step
Solution Approach 1:
The patent performs preliminary validation actions by querying both the source and destination data stores with identical queries before finalizing the migration validation. This preliminary comparison identifies potential data corruption or loss early in the process, allowing for corrective actions before the migration is complete, thereby reducing the risk of undetected data corruption despite multiple transformation steps.
Data Source
AI summary
A system for validating data migrated from a first data store with source data to a second data store for destination data. A comparator is configured to access entity data for a particular entity which has been migrated from a first data store to a second data store. The comparator queries the first data store to a first set of comparison data from the first data store and obtains a second set of comparison data from the second data store. It then compares the first set of data with the second set of data to validate the migration of the data from the first to the second data store.