Now Available: Cloudera Data Science Workbench Release 1.2

Categories: Data Science Machine Learning

 

Cloudera Data Science Workbench (CDSW) is a self-service collaboration platform for data scientists. It offers:

  • Secure access to Cloudera data
  • On-demand compute
  • Support for Python, R, and Scala
  • Workflow automation, version control, and sharing
  • GPU acceleration for deep learning on demand

Now, with Release 1.2, CDSW is easier than ever to deploy and manage. The new release includes many new features:

Easier administration. CDSW is now available as a service for Cloudera Manager, so you can install, upgrade, uninstall, monitor, and configure nodes from a familiar user interface. With usage monitoring and reporting, customers can track user adoption, rationalize licenses, plan resource capacity, view resource usage patterns, and debug resources. Simple installation, configuration, and administration mean faster time to value and lower maintenance costs.

For more detail on user monitoring, read this article on the Cloudera Engineering Blog.

Improved sharing options. In collaborative data science, users need to share projects with one another — to perform tasks in parallel, leverage specialized expertise, for peer review, and for many other reasons. CDSW Release 1.2 provides users with more precise sharing options. Users can share projects with anyone, only with authenticated users, with specific users, or with teams. Administrators can disable anonymous sharing for extra security.

Expanded deployment options. With CDSW Release 1.2, Cloudera adds support for CDSW on RHEL 7.4. In addition to cloud options, customers can now deploy on premises with CDSW with CDH 5.7 or higher with RHEL/CentOS 7.2, 7.3, and 7.4, as well as Oracle Linux 7.3 (for the Oracle Big Data Appliance.) Coming soon: support for SLES 12 and the Teradata Appliance for Hadoop.

CDSW Release 1.2 includes many other enhancements, including all-numeric usernames, usernames, simplified worker node joins, improved Python plotting, and Apache Kudu client libraries.

The software is available for download and trial here.

Learn more about how Cloudera Data Science Workbench makes your data science team more productive.

Did you know that Cloudera is a great platform for deep learning? Read this article on deep learning with Apache MXNet on Cloudera Data Science Workbench. To learn more about how to make deep learning work for your organization, read Deep Learning: A Guide for Enterprise Architects, available here.

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