Launching end-to-end security in 6 months to cut client churn
SK Shieldus· South KoreaDatabricks Data + AI Platform · Delta Lake · Lakeflow Jobs +2
SK Shieldus built an integrated data analytics platform on Databricks in six months, deploying a cancellation-prevention scoring model and a predictive control model for security dispatch using Delta Lake, Lakeflow Jobs and Unity Catalog, improving machine learning model accuracy from under 70% to over 90% and reducing unnecessary dispatches by 2%.
Overview
SK Shieldus built an integrated data analytics platform on Databricks in six months, deploying a cancellation-prevention scoring model and a predictive control model for security dispatch using Delta Lake, Lakeflow Jobs and Unity Catalog, improving machine learning model accuracy from under 70% to over 90% and reducing unnecessary dispatches by 2%.
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Inspect the highlighted sourceThe challenge
SK Shieldus' previous data infrastructure lacked the structure and scalability needed to support advanced data-driven services: data was spread across multiple operational systems in different formats and structures, and each business unit was managed by its own operational IT department, making integrated analysis difficult.
The solution
SK Shieldus adopted the Databricks Data + AI Platform and, within six months, built a unified data analytics platform, deploying a cancellation-prevention scoring model that identifies churn-risk customers and delivers generative AI-powered customization guidance, and a predictive control model that analyzes abnormality signals to determine whether dispatch is needed, built on Delta Lake and Lakeflow Jobs for automated pipelines and monitoring, Unity Catalog for governed data access, and MLflow for model experimentation and tracking.
Reported business value
SK Shieldus improved machine learning model accuracy from less than 70% to over 90%, a 20% increase, reduced unnecessary dispatches by 2% using its predictive control model, reduced call times and improved retention rates through the cancellation-prevention model, and optimized budget operations by reducing hardware and maintenance costs.
Sources
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