Build a watermark-based incremental load in Azure Data Factory, then close its two silent gaps: transactions that commit late and deleted rows, with overlap windows, rowversion and Change Tracking.
A design guide for Azure Data Factory pipelines that survive production: orchestrator and worker pipelines, parameters, idempotent windows, timeouts and retries, concurrency, secrets, monitoring and CI/CD.