How ZS democratized secure ad-hoc analytics with Amazon SageMaker | Amazon Web Services
This blog post is co-written with Kiran Dhamane, Abhishek I S, and Mayur Ghodekar from ZS Associates
Organizations in regulated industries face a persistent tension: give developers the agility they need for ad-hoc analytics, or lock down the environment to meet compliance requirements. In this post, we explore how ZS built a security-hardened Amazon SageMaker environment that balances developer agility with strict governance. The platform now serves 1,000+ daily active users across 200+ SageMaker domains. We walk through the technical architecture, custom domain implementations, and the measurable business impact of democratizing machine learning (ML) access across the organization.
Building a healthcare-grade ML platform
ZS selected Amazon SageMakerStudio as their foundation for enterprise ML operations. The team implemented a comprehensive security framework that integrated their unique security standards directly into the developer experience. This approach let data scientists and analysts across the organization access ML capabilities while maintaining compliance with...
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