Cloudera Machine Learning Powers Collaborative Data Science at Scale with Secure, Self-Service Access to Governed Data Anywhere
PALO ALTO, Calif., September 24, 2019 – Cloudera (NYSE: CLDR), the enterprise data cloud company, today launched Cloudera Machine Learning, the enterprise machine learning service for the new Cloudera Data Platform. Cloudera Machine Learning makes it easy for IT to say yes to self-service data science for business at scale.
Cloudera Machine Learning enables enterprise data science in the cloud
“With Cloudera Machine Learning, businesses can rapidly deploy new ML Workspaces or virtual machine learning environments for teams in a few clicks, providing self-service access to the shared data and tools required for end-to-end machine learning workflows, anywhere,” said
Priyank Patel, Head of Machine Learning Products at Cloudera. “By lowering the barriers to innovation and differentiation with enterprise machine learning, Cloudera Machine Learning enables rapid onboarding and agile experimentation at scale for data science teams.”
The new machine learning service on the Cloudera Data Platform provides data scientists, data engineers, and machine learning engineers with:
- Instant workspaces - deploy new machine learning workspaces for teams in a few clicks, with access to the project environments and resources they need for end-to-end machine learning.
- Rapid replication - provide democratized access to replicate data sets across hybrid and multi-cloud environments while maintaining enterprise data security and governance controls.
- Choose your own tools - provide data science teams’ with access to their favorite, open data science tools while preserving security and minimizing administrative overhead
- Elastic, auto-suspending resources - deliver the scale-out, heterogeneous computing resources data science teams need to get work done fast while maintaining adjustable guardrails that help IT easily manage and optimize infrastructure resources and costs.
- Comprehensive, cohesive user experience - data engineering, model training, experiment tracking, and deploying and managing production models all in one seamless environment, without switching or stitching workflows together with multiple tools.
- Portability and consistency - the liberty to move data and infrastructure anywhere without creating disconnected silos and without changing the consistent user-experience that data science teams rely on for building robust workflows and processes for end-to-end ML.
Cloudera Machine Learning is fully integrated with the Cloudera Data Platform (CDP) including Cloudera Data Warehouse and Data Hub, allowing for the fast delivery of new multi-function analytics and machine learning in any cloud. This makes it possible for businesses to build, manage, and scale intelligent applications fueled by data anywhere—from the Edge to AI. Cloudera Machine Learning also fully capitalizes on the Shared Data Experience (SDX) provided by CDP. Cloudera SDX provides consistent data security, governance and control across all multi-function analytics, for safe, self-service access and discovery of data at enterprise scale.
Cloudera Machine Learning delivers a packaged experience for data engineering and machine learning workflows offered through a combination of consumption and per-user access pricing.
For more information on Cloudera Machine Learning on the Cloudera Data Platform, please click here.
At Cloudera, we believe that data can make what is impossible today, possible tomorrow. We empower people to transform complex data into clear and actionable insights. Cloudera delivers an enterprise data cloud for any data, anywhere, from the Edge to AI. Powered by the relentless innovation of the open source community, Cloudera advances digital transformation for the world's largest enterprises. Learn more at Cloudera.com.
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This press release contains forward-looking statements including, among other things, statements regarding the expected performance and benefits of Cloudera’s offerings. The words "believe," "may," "will," "plan," "expect," and similar expressions are intended to identify forward-looking statements. These forward-looking statements are subject to risks, uncertainties, and assumptions. If the risks materialize or assumptions prove incorrect, actual results could differ materially from the results implied by these forward-looking statements. Risks include, but are not limited to, risks described in our filings with the Securities and Exchange Commission (SEC), including our quarterly and yearly reports that we file with the SEC from time to time, which could cause actual results to vary from expectations. Cloudera assumes no obligation to, and does not currently intend to, update any such forward-looking statements after the date of this release.