Cloudera Debuts Data Science Workbench

Cloudera, which provides an analytics platform built on Hadoop and other open source software, has unveiled the Cloudera Data Science Workbench, a new self-service tool for data science on Cloudera Enterprise. The Cloudera Data Science Workbench is currently in beta.

Based on the company's recent acquisition of the data science startup, Cloudera says, Data Science Workbench allows data scientists to use their favorite open source languages - including R, Python, and Scala - and libraries on a secure enterprise platform with native Apache Spark and Apache Hadoop integration, to accelerate analytics projects from exploration to production.

Cloudera is focused on improving the user experience for data science and engineering teams and, in particular, those that seek to scale their analytics using Spark for data processing and machine learning, said Charles Zedlewski, senior vice president, Products, at Cloudera. The acquisition of and its team provided a strong foundation, and Data Science Workbench helps make self-service data science at scale available to Cloudera customers.

The workbench helps organizations stay compliant with out-of-the-box support for full Hadoop security, including Kerberos. and runs on-premises or in the cloud, wherever an organization manages its data.

Beyond the extensive Python and R ecosystems, as open data science expands to include deep learning frameworks like Tensorflow, Microsoft Cognitive Toolkit, MXnet, BigDL, and more, data science teams are looking for ways to bring these tools to their data, which is increasingly stored in Hadoop environments Cloudera Data Science Workbench delivers a safe and secure environment to combine the latest open source innovations with the unified platform Cloudera customers trust, the company says.

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