Overview
The freedom data science teams need delivered by a cloud-native service that works for IT.
Cloudera AI (formerly Cloudera Machine Learning) enables enterprise data science teams to collaborate across the full data lifecycle with immediate access to enterprise data pipelines, scalable compute resources, and access to preferred tools. Streamline the process of getting analytic workloads into production and intelligently manage machine learning use cases across the business at scale.
Cloudera AI optimizes workflows across your business with native and robust tools for deploying, serving, and monitoring models. With extended SDX for models, govern and automate model cataloging and then seamlessly move results to collaborate across Cloudera experiences, including Cloudera Data Warehouse and Cloudera Operational Database.
For data scientists
Optimize the AI data lifecycle and operationalize machine learning models across the business with transparent and repeatable workflows that work for everyone.
For IT leaders
Give your data science teams the resources they need to experiment, iterate, and impact the business anywhere, without compromising agility, security, or governance.
Cloudera AI use cases
TAKE AI FROM CONCEPT TO REALITY
SCALE MACHINE LEARNING WITH MLOPS
ENABLE EXPLORATORY DATA SCIENCE
Take AI from concept to reality
Reduce your time to value with Accelerators for ML Projects (AMPs).
AMPs are designed to jumpstart your AI initiatives by providing tailored solutions for specific use cases within Cloudera AI. They enable users to quickly achieve success by offering high-quality, pre-built reference examples that can be easily adapted to your unique requirements, reducing time to value for your projects.
Scale machine learning with MLOps
Benefit from improved transparency, collaboration, and ROI with MLOps.
MLOps helps you capitalize on early successes and scale up, following steps to keep existing models current, and establishing controls to maintain data security and governance through the entire production ML and AI lifecycles.
Enable exploratory data science
Compress the space between data exploration and business action.
Cloudera offers a complete platform that provides data science teams with “certified datasets,” as well as consistent and robust tooling to make data explorations, ad-hoc data science, and insight generation as fast as possible.
Deploy workspaces in a few clicks, giving data science teams access to the project environments and automatically elastic compute resources they need for end-to-end AI without waiting.
With Cloudera AI, administrators and data science teams have full visibility from data source to production environment—enabling transparent workflows and easy collaboration across teams securely.
Data scientists shouldn't have to switch between tools to discover, query, and visualize data sets. Cloudera AI offers all of these capabilities via the Data Discovery and Visualization feature, a single UI for all your exploratory data science needs.
AMPs are Cloudera AI projects that can be deployed with one click directly from Cloudera AI. AMPs enable data scientists to go from an idea to a fully working use case in a fraction of the time. It provides an end-to-end framework for building, deploying, and monitoring business-ready AI applications instantly.
Cloudera AI’s MLOps capability enables one-click model deployment, model cataloging, and granular prediction monitoring to keep models secure and accurate across production environments.
Deliver insights with a consistent and easy-to-use experience, featuring intuitive and accessible drag-and-drop dashboards and custom application creation.
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Experience Cloudera AI for yourself
Cloudera AI deployment options
Deploy Cloudera AI anywhere with a cloud-native, portable, and consistent experience everywhere.
Cloudera on cloud
- Multi-cloud ready: Don’t get locked into a single cloud provider. Power your AI initiatives holistically with data from anywhere.
- Scalable: Leverage scalable and auto-suspending compute resources that you only pay for while in use.
- Full lifecycle integration: Seamlessly and securely share workloads and outputs across Cloudera experiences including Cloudera Data Engineering and Cloudera Data Warehouse.
Cloudera on premises
- Cost-effective: Optimized resource utilization from disaggregated storage affords cost-efficiencies across the cluster.
- Optimized performance: Meet your SLAs every time with workload isolation and multi-tenancy for critical workloads.
- Collaborate effectively: Securely share workloads, data, and results across teams at every stage of the data lifecycle.
What customers say about Cloudera AI
“Integrates seamlessly with the other Cloudera experiences, enabling rapid realization of insights from your data. I especially appreciate the flexibility and openness.”
Analytics Solution Architect
Energy and Utilities Industry
“One-stop-shop for your data science needs. Managing multiple sessions, automating data pipeline jobs, and even creating machine learning apps are all easy and intuitive.”
Model Development Expert
Services Industry
“Excellent platform for any type of ML and Data engineering project. Provides an easy path to develop and test code as well as ML performance tracking.”
Big Data And Analytic Architect
Miscellaneous Industry
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