
Why Data Teams Struggle With Real-Time Decisioning
transcript
show notes
Most data teams build pipelines that work beautifully for yesterday’s decisions but fail when the clock ticks forward. In this episode, we look at how major retailers and logistics firms are shifting from batch processing to real-time event streams. We examine the specific architecture changes required to move from nightly reports to sub-second inference, and why the bottleneck is rarely the model itself—it’s the latency in getting fresh features to the edge. If you’re still relying on static snapshots for dynamic pricing or fraud checks, this breakdown of the real-time stack will show you where the friction lives.
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