Data Reconciliation in migration refers to the process of verifying and validating the consistency and accuracy of data between the old system (source) and the new system (target) after data migration. The goal is to ensure that all data has been correctly transferred, that there are no discrepancies, and that the integrity of the data is maintained throughout the migration process.
Key Objectives of Data Reconciliation in Migration :
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Data Integrity Verification:
- Ensure that the data in the new system is complete and matches the original data in the old system.
- The accuracy and completeness of the migrated data are critical for business operations and analytics.
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Identifying Discrepancies:
- Reconciliation helps identify any mismatches, missing records, or corrupt data during or after the migration process.
- It helps detect issues like data truncation, formatting errors, or misaligned fields.
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Validation of Business Rules:
- Ensure that the data in the new system follows the same business rules, constraints, and relationships as the original data.
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Compliance and Reporting:
- Ensures that the data migration process adheres to regulatory requirements, ensuring auditability and data traceability.
