When migrating data, reconciliation and data validation are not just technical steps—they are critical components that ensure the success and integrity of your business operations. Data reconciliation helps verify that all information has been accurately transferred to the new system, leaving no room for costly errors or data loss.
Skipping or overlooking these processes can lead to flawed insights, operational disruptions, and reputational risks. By prioritising data reconciliation and validation, you safeguard your business and set the foundation for informed decision-making.
Reconciliation and validation processes are essential to maintaining data accuracy and demonstration of controls across systems when migrating data. Below are the critical steps we take at Elwyn Consulting to ensure the integrity of your data is maintained during the migration.
One of the foundational steps in data reconciliation is performing a detailed comparison of values. This involves examining each field in the source system and comparing it directly with the corresponding field in the target system, focusing on critical fields and key metrics for business operations.
This step is essential for detecting anomalies, errors, or discrepancies that might have occurred during migration. By ensuring field-level accuracy, you can identify and fix mismatches before they become more significant issues.
Validation checks are non-negotiable for verifying the integrity of your data. Completeness checks confirm that no data was omitted during the migration process, while accuracy checks ensure that every value matches its intended format and context.
Conducting these checks ensures that every record is present and correctly represented in the target system.
Data ecosystems often rely on relationships between different tables or entities in a database. For example, a customer record in one table might be linked to purchase orders or payment information in related tables.
Consistency checks ensure that these relationships remain intact post-migration. Any discrepancies in related datasets—missing references, orphaned records, or mismatched data points—can severely impact workflows and reporting accuracy.
Data pipelines often consist of several stages, from extraction and transformation to loading into the target system. It’s critical to validate and monitor the flow of data through every step of this pipeline.
This means ensuring data integrity as it passes through transformations, filtering, or cleaning processes. Each component in the pipeline must not only accurately process the data but also maintain compatibility with subsequent stages.
Finally, thorough reconciliation requires confirming that all data has been successfully loaded into the target system. Beyond counting records, this step verifies that dependent or linked records have also been fully migrated. Failure to load even a small subset of data can lead to incomplete datasets and downstream issues.
Avoid the pitfalls of data migration projects that overrun budgets, miss deadlines, or fall short of your goals. At Elwyn Consulting, we bring the expertise and insight of Australia’s top data migration specialists. We’ll work with you to reconcile and validate your data through the migration to ensure your transformation project achieves outstanding results.
Whether you're upgrading software, migrating databases, or integrating new tools, following these reconciliation and data validation steps will ensure the integrity of your data, reduce the risk of errors, and ensure your team maintains trust in your systems.
Not sure where to begin? Contact our team of data specialists, and we will safeguard your data's integrity from day one.
Angel Place, Level 17
123 Pitt Street
Sydney NSW 2000
