Handling Late Data and Watermarks: Accuracy in Real-Time Stream Processing

The Hidden Cost of Speed

You’re running a real-time analytics dashboard tracking user clicks across 50 million daily active users. Events flood in from mobile apps, web browsers, and IoT devices worldwide. Your system computes click-through rates every 10 seconds with impressive sub-second latency. Then your VP notices something odd: yesterday’s hourly report shows 2% more clicks than the real-time dashboard reported. Where did those extra clicks come from?

Welcome to the late data problem—the silent accuracy killer in stream processing systems. Those “missing” clicks arrived late, after your system already computed and published results. Your dashboard was fast but wrong. This is where watermarks become your precision instrument for balancing speed against completeness.