GreenLake for ML and Analytics

The HPE Ezmeral Unified Analytics solution modernizes legacy data and applications to optimize data-intensive workloads from edge to cloud to deliver the scale and elasticity required for advanced analytics.

Organizations in every industry are looking to leverage AI and ML to harness the power of their data and deliver business innovation through data science. But even when they achieve some measure of success with machine learning pilot programs, many organizations face challenges when they seek to scale these programs to production: security concerns, legacy hardware, siloed data and workflows, inefficient processes, and daunting costs.

To deliver the value of ML and data science to your enterprise, the HPE GreenLake platform delivers an enterprise-grade ML cloud service that enables developers and data scientists to rapidly build, train, and deploy ML models—from pilot to production, at any scale. This solution comprises an optimized hardware stack and is powered by HPE Ezmeral ML Ops. It provides data scientists with self-service access to a sandbox environment for prototyping and testing, to eliminate IT provisioning delays, ensure repeatability, and accelerate time-to-value.

To help you mine continuous streams of value locked in your data, HPE GreenLake delivers a trusted, enterprise-grade AI/ML and analytics cloud-like experience so you can accelerate your data modernization initiatives, from edge to cloud. With a cloud-native architecture, support for open source data science tools, and AI accelerators and frameworks, it provides choice and an elastic, unified analytics platform for data and applications on-premises, at the edge, and in public clouds. The consistent experience helps data, IT teams, developers, and analysts simplify the complexities of machine learning lifecycles and data management at scale, leading to better, faster decisions no matter where your data resides.