Cloudera Data Platform
Data Services for Machine Learning
EMA Top 3 award-winning products enable data scientists, data engineers, DevOps teams, application operators, and developers to rapidly provision, manage, scale, move, and terminate compute and storage resources in a reliable, secure, and cost effective manner. The ability of a platform to share critical infrastructure resources like GPU, TPU, CPU, RAM, and storage, between teams and projects enables organizations to squeeze the most value out of these resources and therefore constitutes a crucial requirement for EMA Top 3 products. To ensure optimal compliance, performance, and security, EMA Top 3 products need to support the policy-driven placement and management of data science workloads across data center infrastructure, multi-cloud EMA Top 3 award winners in the End-to-End Machine Learning Infrastructure category need to enable current staff to use their existing development and operations tools and infrastructure in the most impactful manner. This must enable each persona to focus on its individual set of key tasks without having to learn new tools, languages, or understanding the inner works of Kubernetes. |
Why Cloudera Data Platform Received the EMA Top 3 Award
The Cloudera Data Platform received the EMA Top 3 award for enhancing the productivity of data scientists and data engineers by providing an ultimate level of consistency in terms of data access, pipeline management, data analytics, and machine learning. Data scientists and data engineers receive a unified set of data APIs that work across all data sources within the corporate data center, the public cloud, and edge locations. The Cloudera Data Platform also delivers standardized but customizable tools and frameworks for data scientists (Cloudera Machine Learning) and data engineers (Cloudera Data Engineering) to directly leverage any data across the organization in a completely consistent manner. This consistency is crucial when it comes to introducing a data-driven culture across the organization as it enables the reuse of machine learning models without significant customization for each instance, even if the data sources are located on different public clouds, data centers, or edge locations. The Cloudera Data Platform allows organizations to optimally place data and application workloads based on cost, performance, and compliance considerations, without breaking existing data pipelines and while retaining central governance across all data. This can bring significant cost advantages within machine learning scenarios, as it enables demanding workloads such as “model training” to access pools of specialized hardware such as GPUs, TPUs, or high performance storage, while the completed models can move to lower-cost infrastructure. |
Website: Cloudera Data Platform
Business Impact
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