Case Study: SK Shieldus achieves faster, more accurate security analytics with Databricks

Launching end-to-end security in 6 months to cut client churn

SK Shieldus, South Korea’s leading converged security company, wanted to modernize its legacy data environment to support more responsive, customer-centric security services. But fragmented systems, inconsistent data formats, and poor collaboration across teams made it difficult to build the advanced machine learning models needed for churn prevention, incident detection, and real-time risk response.

By adopting the Databricks Data Intelligence Platform, SK Shieldus built a unified data analytics platform in just six months, bringing analytics and AI onto a single foundation. Using Databricks, the company improved machine learning model accuracy by more than 20%, reaching over 90% overall accuracy, helping it accelerate proactive security capabilities and strengthen client retention efforts.

SK Shieldus

SK Shieldus

Data Group Leader