Real-Time Data Quality: Handling Late Data, Reconciliation, and Alerting
This article explores data quality challenges in real-time data warehouses, covering timing agreements for late-arriving data, reconciliation techniques using Flink and Paimon, SQL-based checking strategies, alerting with actionable details, and iterative quality validation processes.
