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Data reconciliation is a process that verifies data migration by comparing source and target data to ensure correct transfer. It has three key steps: capture source data, scrub data by validating, standardizing, and enhancing values, and transform data into the target schema and structure before loading into the data warehouse. Reconciled data forms the single authoritative source for decision making, while derived and aggregated data are formatted views of reconciled data to support end users.










