Case Study: Sevatec achieves accelerated data access and scalable machine learning for federal agencies with Databricks

Sevatec - Customer Case Study

Sevatec is a high-technology services firm that supports mission-critical applications across federal agencies including Homeland Security, DoD, DOT, and State. The company faced major data challenges: ingesting and preparing data from 30+ disparate systems, supporting a 2,000+ user community with varied skills, lacking a single view for data science, running RStudio on a single node that prevented scaling, and managing multiple disjointed tools that created DevOps complexity and I/O‑driven SLA issues.

By adopting the Databricks Unified Analytics Platform, Sevatec streamlined data engineering on a fully managed cloud platform, democratized access to data via APIs and connectors (cutting ingest times from hours to minutes), and enabled machine learning at scale across the full dataset. Automated, secure cluster management removed much of the DevOps burden, while an interactive workspace fostered cross-functional collaboration and faster data science experimentation, improving scalability and operational performance.

Sevatec

Rakesh Pol

BI Architect