Case Study: Zoetis cuts diagnostic data processing time by 93% with Toptal

Zoetis cuts diagnostic data processing time by 93% with Toptal

Zoetis, a global animal health company, needed to modernize its fragmented and high-cost diagnostics data ecosystem. The aging system caused significant latency in diagnostic results and lacked the scalability to handle increasing data volumes. Toptal was engaged to provide data engineering services to address this challenge.

Toptal assembled a specialized team to redesign the platform using Databricks, Azure, Python, and SQL. The solution streamlined data ingestion and transformation, reducing latency from 15 minutes to under 60 seconds. This modernization effort cut data processing time by 93% and reduced platform operating costs by 67%, saving an estimated $325,000 annually in cloud hosting while providing a scalable system for future growth.

Zoetis