Organizations have been investing in artificial intelligence (AI) and machine learning (ML) for some time, with many turning to cloud-based resources for the data and analytics capabilities required for these initiatives. Transitioning workloads to the cloud is a complex process, but organizations believe that the benefits will outweigh the costs and risks once their transformation to a cloud-first AI/ML model is complete.
However, this journey is not without its challenges and opportunities. To increase the probability of success, it’s essential to understand and manage risk, including taking strategic risks where outcomes can be predicted. A transformation and adoption framework can help organizations navigate this journey by providing a structure and common language to understand where they are in their journey, benchmark against best practices, and prioritize next steps.
HPE Edge-to-Cloud Adoption Framework is designed to help organizations be more successful with AI/ML pilots and take their transformation to the next level with confidence. This framework enables organizations to navigate the complexities of migrating workloads to the cloud and helps organizations to be more successful in their AI/ML initiatives.
Hewlett Packard Enterprise (HPE) offers a wide range of products and services that help organizations to unlock the power of data through artificial intelligence (AI), machine learning (ML), and analytics. These solutions enable organizations to gain valuable insights from their data and make data-driven decisions that can improve their performance and drive digital transformation.
Unlock the Power of Data with HPE’s AI, ML, and Analytics Solutions
Hewlett Packard Enterprise (HPE) offers a comprehensive, flexible, and cost-effective solution for consuming IT resources through its AI, ML, and analytics solutions. With HPE’s solutions, customers can unify and share analytics, take control of their data, and achieve up to 35% more efficiency than the public cloud using the industry’s first Kubernetes-native unified, modern, hybrid analytics and data lake platform.
Operationalize and Automate Machine Learning
With HPE’s solutions, customers can accelerate development and standardize and operationalize the machine learning lifecycle from planning to model development, training, deployment, and monitoring. This allows customers to provision testing and development environments in minutes and gain targeted, rapid innovation that can evolve quickly in response to changing data.
Scale and Modernize AI Infrastructure
HPE’s solutions also allow customers to deploy converged high-performance computing (HPC)/AI workloads on GPUs and high-performance clusters with predictable, transparent costs. Customers can quickly scale as needed with next-generation architecture and, using continuous monitoring, can right-size capacity and even enable capacity-bursting on-site, on demand.
Extend Resources with AI and Data Expertise
With HPE’s solutions, customers can also tap into the broad and deep set of HPE experts in AI/machine learning, analytics, HPC, cloud, Edge/IoT services and position their developers and data scientists for successful AI solution deployment. HPE’s comprehensive support enables IT operation teams to bridge their knowledge gap and sustain their AI solutions at enterprise scale. As a leader in IDC’s AI IT Infrastructure Services MarketScape, HPE is helping hundreds of global customers accelerate their data-first modernization journey.
HPE GreenLake for data fabric
Realize the potential of all your data wherever it lives with an edge-to-cloud logical data store delivered as a fully managed service by unlocking the potential of globally unified data. 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 the insights that you need to innovate and drive your business. A single solution that combines the best edge-to-cloud experience with unified hybrid data so you can accelerate business innovation. This fully managed solution 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.
Unified analytics HPE Ezmeral
Unified Analytics architecturally optimizes and leverages the industry’s first cloud-native solution on-premises, enabling you to scale up Apache Spark lakehouses and speed up AI and ML workflows. Spanning from edge to hybrid cloud, this data platform offers a consistent environment to avoid silos and make data engineering easier.
The HPE GreenLake end-to-end data science platform for ML Ops brings DevOps agility to the machine learning lifecycle—speeding data science workflows and enabling data scientists to accelerate the time to value of ML projects. This service is powered by HPE Ezmeral ML Ops.
HPE GreenLake for HPC is a consumption-based solution that is fully managed and operated for you, just like public cloud. But you can also choose from the world’s most-proven, market-leading HPC systems, pre-integrated and optimized by HPE and partners for your AI modelling, training, and simulation workloads. And with built-in operational support, you have access to the right level of expertise for improved ROI.
AI and analytics solutions
Together with our alliance and ISV partners, HPE delivers industry-focused AI solutions, tools, and services with HPE GreenLake deployment options. A proven global leader, HPE helps you rapidly design and deploy your AI and analytics solutions, such as HPE GreenLake for Epic and Splunk, or AI solutions for banking, manufacturing, or healthcare.
Storage services for AI and analytics
Address your growing unstructured data needs for AI with storage solutions from HPE GreenLake featuring Scality and Qumulo. Scale and manage billions of files with instant control and the ability to perform actionable analysis quickly. Features like deep and rich data analytics built into the file system help you understand your data in ways you never could before.