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Most enterprises store diverse data types across multiple platforms, such as on-premises data centers, multiple clouds, and at the edge. Each environment becomes an independent silo that restricts access to the data and the insights they contain. This means slower time to modernize analytics and gain the insights that you need to innovate and drive your business.
The HPE GreenLake platform offers a fully managed, on-premises service containing an analytics-ready data fabric for hybrid environments. From a single management view, it allows you to set up, administer, and manage globally distributed data sets across edge-to-cloud deployments. It lowers risk by providing infrastructure in a pay-per-use model, while HPE Ezmeral Data Fabric modernizes analytics and data management, unifying different data types across on-premises, multi-cloud, and edge, and delivering seamless access to a trusted source of data.
Accelerate data-first modernization and realize the potential of all your data wherever it lives with an edge-to-cloud logical data store delivered as a cloud service.
This HPE GreenLake cloud service delivers the first edge-to-cloud analytics-ready logical data store with superior scalability, built-in data services, and superior economics.
Edge-to-cloud experience for your data
This single solution combines the best edge-to-cloud experience with unified hybrid data so you can accelerate business innovation. As a managed data fabric solution, it reduces the cost of analytic initiatives by providing a high-performance approach to your data that can be managed, secured, and deployed edge to cloud. The HPE GreenLake platform can deliver superior flexibility, scalability and control of data solutions with a cloud service consumption model on premises.
Corporate-wide access to data increases collaboration and data sharing across globally distributed teams. The single data store enables data reuse by multiple use cases, applications, and users, which means that less infrastructure needs to be reserved for individual workloads or file types. And with industry-standard APIs fully supported, existing access patterns for users and apps can be preserved without requiring low-value refactoring.
Simplify hybrid data operations
Monitor and manage hardware, software, and services through a single management view. Create automated policies once to apply across global datasets for multi-tenancy, data resilience, security, and data placement. In addition, layering on certified open-source tools allows for real-time, in-place analytics and reduces time spent integrating and configuring community open-source tools.
Gain insights from all your data
Power your data scientists and data engineers with unified, trusted data and a single platform that supports a broad range of APIs, languages, and protocols addressing multiple analytics use cases: data analytics, AI/ML, and edge analytics. Get freedom and flexibility in where your applications are deployed, processing a full range of data types and workloads for your AI/ML, analytics, datalakes, datalake houses, data warehouses, or Hadoop instances.