Data Validation Tool for Database Migration Accuracy
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Solution Overview
Problem
Conventional data migration services lack mechanisms for validating data during migration from a source database to a target database, leading to manual spot checks that are inefficient and unreliable, especially for large and dynamically changing datasets.
Innovation Solution
A data validation tool that integrates with data migration services to validate data by comparing source and target databases at various levels of granularity, using partitioning and configurable validation rules to ensure accurate data migration and provide validation metrics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual spot checks are used to validate migrated data, then some data accuracy can be verified, but the validation is inefficient and unreliable for large datasets
Solution Approach 1:
The patent divides the data validation process into multiple levels: row-level validation, partition-level validation, and database-level validation. This segmentation allows comprehensive validation of large datasets by breaking them into manageable units, improving both reliability and efficiency simultaneously
Solution Approach 2:
The patent performs validation rules configuration and partitioning before the actual data migration. This preliminary action ensures that validation is already prepared and can execute automatically during migration, eliminating the need for manual spot checks and improving validation reliability
2Measurement precision
If comprehensive data validation is performed on large datasets, then data accuracy is improved, but the validation process becomes complex and resource-intensive
Solution Approach 1:
The patent segments the validation process into hierarchical levels (row, partition, database) with different validation rules at each level. This allows comprehensive validation without overwhelming complexity, as each level handles specific aspects independently
Solution Approach 2:
The patent applies different validation strictness levels - some validation rules are mandatory while others are optional. This partial action approach ensures critical data accuracy without requiring all possible validation checks, reducing overall process complexity
3Reliability
If data validation is performed during migration of large datasets, then confidence in data accuracy increases, but the migration time increases
Solution Approach 1:
The patent prepares validation rules and partitions before migration begins. This preliminary action allows validation to execute concurrently with migration operations, minimizing additional time while maximizing data migration confidence
Solution Approach 2:
The patent performs validation at selective levels rather than exhaustive validation of every data element. This partial validation approach provides sufficient confidence in data accuracy without the time cost of complete validation
Data Source
AI summary
A method and system for validating data migrated from a source database to a target database and storing validation metrics resulting from validating the data are described. The system receives validation information to be used to validate data to be migrated from a source database to a target database. The system validates the data using the validation information and stores validation metrics resulting from validating the data.