Real-time analytics pipeline
5M+ daily events at sub-millisecond latency — live dashboards and automated business alerts.
Existing nightly ETL jobs left the business blind to intra-day trends. Teams had no visibility into live conversion rates, cart abandonment spikes, or inventory shortfalls until the following morning — by which point revenue was already lost. The data team spent 40% of their time maintaining fragile batch scripts.
We built a streaming pipeline on Databricks with Delta Live Tables, ingesting Kafka events from 14 application services in real time. Transformations run as structured streaming jobs with schema evolution and late-arrival handling built in. Power BI connects via DirectQuery for live dashboard refreshes. Databricks SQL alerts fire Slack and email notifications within 30 seconds of threshold breaches across 12 tracked KPIs.
The pipeline processes 5M+ events per day with end-to-end latency under 1ms for aggregated metrics. The data team's maintenance burden dropped 70%. The business detected and resolved a payment gateway issue within 8 minutes — previously it would have gone unnoticed overnight.
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