Case Study: White Ops achieves real-time ad-fraud detection and faster algorithm development with Snowflake

White Ops Uses Snowflake to Make Real Time Decisions Against Digital Ad Fraud

White Ops is a cybersecurity company that detects and prevents sophisticated ad and malware fraud by distinguishing human from bot activity across advertising, publishing and enterprise systems. Their challenge was processing and analyzing massive, constantly changing real‑time data: researchers were blocked by a Hadoop/MongoDB pipeline that required custom map‑reduce jobs, creating bottlenecks, long latencies and limited access to data (often 24+ hour delays).

By adopting the Snowflake Elastic Data Warehouse, White Ops consolidated diverse data, used standard SQL, and leveraged separation of compute and storage to scale on demand and democratize analytics. The result: algorithm development latency dropped from 24+ hours to under two hours, QA and system health improved, and teams gained deeper, more accurate and widely accessible data—speeding releases, enabling safe experimentation, and strengthening fraud detection.

White Ops

Tamer Hassan

Co-Founder And CTO