Cloudera to Accelerate Data Science and Machine Learning for the Enterprise with New Data Science Workbench
Collaborative, Self-Service Environment for Secure Data Exploration, Visualization, and Modeling Brings Data Scientists, Analysts, and Business Teams Together
SINGAPORE, March 15, 2017 – Cloudera, the provider of the leading global platform for machine learning and advanced analytics built on the latest open source technologies, today unveiled Cloudera Data Science Workbench, a new self-service tool for data science on Cloudera Enterprise which is currently in beta. Based on the company's acquisition of data science startup Sense.io last year, 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, in particular those who want to scale their analytics using Spark for data processing and machine learning,” said Charles Zedlewski, senior vice president, Products at Cloudera. “The acquisition of Sense.io and its team provided a strong foundation, and Data Science Workbench now puts self-service data science at scale within reach for our customers.”
Cloudera Data Science Workbench’s benefits include:
For data scientists -
- Use R, Python, or Scala with your favorite libraries and frameworks, directly from a web browser.
- Directly access data in secure Hadoop clusters with Spark and Impala.
- Share insights with your whole team for reproducible, collaborative research.
For IT professionals -
- Give your data science team the freedom to work how they want, when they want.
- Stay compliant with out-of-the-box support for full Hadoop security, especially Kerberos.
- Run on-premises or in the cloud, wherever you manage your data.
As open data science expands beyond the extensive Python and R ecosystems 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.
“By providing ready access to data, Cloudera Data Science Workbench decreases time to value of AI applications delivered with the DataRobot automated machine learning platform,” said Jeremy Achin, DataRobot CEO and co-founder. “DataRobot is fully integrated which allows Cloudera users to increase business value from the world's best algorithms and data science techniques through an easy to use interface.”
“Our customers’ IT groups often struggle to onboard data scientists to shared environments because their needs are so diverse, especially where open source tools are involved. The result is usually duplication, analytic silos, and limited security and governance. Meanwhile, data scientists are constantly looking to scale their work to larger datasets and more powerful compute platforms,” continued Zedlewski. “With Data Science Workbench, Cloudera is helping IT groups and data scientists work together, bringing more users to shared environments in a way that delivers both flexibility and compliance.”
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