Validate data mapping between source and target systems.
Perform schema comparisons to ensure alignment of database structures.
Conduct field-by-field comparisons to verify data accuracy.
Perform data profiling and quality checks to identify inconsistencies or errors.
Validate data transformation logic to ensure it meets business rules.
Ensure data integrity during migration and integration processes.
Create and manage test data sets that reflect real-world scenarios.
Use synthetic data generation tools to create diverse test data.
Map test data to test cases for comprehensive coverage.
Leverage automation tools for data validation and testing.
Implement self-healing scripts to adapt to changes in data structures.
Use AI-driven tools for test case prioritization and early performance insights.