What the Client Was Facing
A SaaS analytics company was generating 10M events per day but had no real-time processing capability. All analytics were batch-processed overnight, meaning customers saw data that was 24 hours old. Churn was increasing as competitors launched real-time dashboards.
What ZippyOPS Was Engaged To Do
ZippyOPS was brought in to design and implement a solution addressing the root causes of the client's challenges — delivering measurable outcomes within a fixed engagement timeline. Our team worked embedded with the client's engineers throughout the entire project.
How We Solved It
ZippyOPS designed and implemented a real-time streaming pipeline — Kafka for event ingestion, Flink for stream processing, BigQuery for analytical storage and a dbt layer for business-logic transformations. Looker served dashboards with sub-minute data freshness.
Technologies Used
Measurable Outcomes Delivered
Customer-facing data freshness reduced from 24 hours to under 60 seconds
Real-time analytics feature launched — directly credited with winning 3 enterprise contracts
Pipeline handles 10M+ events/day with 99.9% delivery guarantee
Infrastructure cost 40% lower than equivalent batch approach
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