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CDP Private Cloud is introducing new analytic experiences targeting the main pillars of every data analytics platform, starting with Cloudera Machine Learning (CML) and Cloudera Data Warehouse (CDW). These experiences have been developed from the ground up as containerized services orchestrated by Kubernetes.  

With this new architecture,  CDP can provision and scale these analytics in minutes and allocate just enough resources to meet current demand, including peak loads.  CML and CDW also feature new end-user interfaces to simplify the end-to-end workflows of their respective data analytics domains.

Join us for this webinar to understand how CDP Private Cloud:

  • Offers an easy, scalable data mart with a rich SQL editor in CDW

  • Allows users to create and visualize complex job pipelines in CML

  • Secures and governs these integrated analytics with Cloudera SDX


Director, Product Marketing

Sushant Rao


Sushant Rao is an expert in the areas of analytics, cloud, and software-defined technologies. He has been working on enterprise software and cloud services for companies such as VMware, HP Software as well as numerous startups. Currently, Sushant leads CDP Product Marketing at Cloudera and is responsible for product messaging and overall GTM strategy.

Director of Product Management

David Bao

Director of Product Management

Sid Shaik


Sid is responsible for driving product strategy for Cloudera’s Cloud Datawarehouse offering. Over the last 20 years, Sid has built and sold databases in various companies. Most recently, he founded a Silicon Valley startup-- Performance Sherpa— in which his team automated IT performance engineering function in large B2C businesses. Prior to that, he worked as a product manager at Yahoo! and Qubole, managing product strategy for petabyte scale databases on private and public clouds. Before that, he worked at Teradata-Aster and Oracle in Engineering, IT, Pre-Sales, Business Development and Customer support. Sid loves the creative process of discovering, defining and solving high impact technology problems in large markets and scaling product businesses within those markets.

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