data-reconciliation

Data reconciliation compares records from multiple sources using defined keys to identify value mismatches, duplicates, and orphaned records, producing detailed exception reports with suggested resolution actions for data stewards.

Duplicate analysis and orphan record reporting scan individual datasets to identify duplicate entries and highlight records present in one system but missing from another, ensuring data consistency across systems.

You can compare source and target CSV files by specifying a matching key, such as transaction_id, and the Skill will calculate match rates while reporting any value mismatches in fields like amount.

Yes, you can regularly reconcile financial transaction data between accounting software and bank statements to ensure all entries are accounted for and match precisely, preventing financial errors and compliance issues.

Data reconciliation operates entirely on provided datasets to ensure data consistency and integrity, requiring no external dependencies or components to identify discrepancies and produce exception lists.

Data reconciliation requires defined key fields to compare records accurately; if datasets lack consistent matching keys, the tool cannot effectively calculate match rates or identify value mismatches and orphaned records.