Scenario: Your company is merging data from two different databases into a single system. How would you apply data quality assessment techniques to ensure that the merged data is consistent and reliable?

Data reconciliation involves comparing and resolving inconsistencies between datasets from different sources. By applying data reconciliation techniques, you can identify discrepancies in data attributes, resolve conflicts, and ensure consistency and accuracy in the merged dataset. This process is essential for integrating data from disparate sources while maintaining data quality and integrity.