Hewlett Packard Enterprise Fuels Data-Driven Digital Transformation with New Products and Partnerships for HPE Ezmeral Software

Hewlett Packard Enterprise (NYSE: HPE) today announced advancements to the HPE Ezmeral software portfolio, with new products and partnerships designed to help organizations unify access to data, from edge to cloud, to fuel their digital transformation initiatives. Together, the HPE Ezmeral portfolio provides customers with an end-to-end hybrid cloud analytics platform that improves quality, repeatability, throughput, and time to value for their AI/ML, analytics and data-intensive workloads. Today’s updates include the following:

• HPE Ezmeral Data Fabric – Now available as a standalone offering in addition to being available as an integrated component of the HPE Ezmeral Container Platform and HPE Ezmeral Machine Learning Operations (ML Ops). The HPE Ezmeral Data Fabric brings a persistent storage layer to streamline the entire machine learning model lifecycle across on-premises, public cloud, hybrid cloud, and edge environments.
• A new HPE Ezmeral Technology Ecosystem program, which includes industry leading ISVs such as Dataiku, MinIO, H2O.AI, Rapt.AI, Run:AI, Sysdig, and Unravel, that have validated their applications on HPE Ezmeral, allowing customers to more rapidly create streamlined analytics environments.
• A new HPE Ezmeral Marketplace available to customers that brings the top ISVs and open-source projects such as Apache Spark, Tensorflow, and many more, to enterprises looking to modernize their workloads to be cloud-native.

“HPE Ezmeral is invaluable to our customers that are now embracing a digital-first strategy, as is evident with our continued growth into new enterprise accounts,” said Kumar Sreekanti, CTO and Head of Software, HPE. “The enterprises that use data and artificial intelligence effectively are better equipped to evolve rapidly in a dynamic, constantly changing marketplace. The separate HPE Ezmeral Data Fabric data store and new HPE Ezmeral Marketplace provide enterprises with the environment of their choice, and with visibility and governance across all enterprise applications and data through an open, flexible, cloud experience everywhere.”

Enterprises are looking to mature their data analytics capabilities and processes to build an analytics factory that can rapidly create applications and drive initiatives that will help them differentiate their organization in the marketplace. To accomplish this, they need to employ an industrialized approach to data science to support many users, tools, and steps in order to deliver an end-to-end, automated analytics solution to improve quality and accelerate time to value for the business.