Late data: when real-time isn't real-time

Why numbers change after the fact and how to keep trust: event time against processing time, watermarks and their strategies, sizing lateness from a measured distribution, windows and late events, patching against reprocessing, versioned results, a production pipeline with daily finalization, T+1 and T+7 reporting, and the dashboard mistakes to avoid.