Big Data Analytics on AWS: Getting Started with Big-Data-as-a-Service

Presented by

Anant Chintamaneni, Vice President, Products, BlueData; Tom Phelan, Chief Architect, BlueData

About this talk

So you want to use Cloudera, Hortonworks, and MapR on AWS. Or maybe Spark with Jupyter or Zeppelin; plus Kafka and Cassandra. Now you can, all from one easy-to-use interface. Best of all, it doesn't require DevOps or AWS expertise. In this webinar, we discussed: -Onboarding multiple teams onto AWS, with security and cost controls in a multi-tenant architecture -Accelerating the creation of data pipelines, with instant clusters for Spark, Hadoop, Kafka, and Cassandra -Providing data scientists with choice and flexibility for their preferred Big Data frameworks, distributions, and tools -Running analytics using data in Amazon S3 and on-premises storage, with pre-built integration and connectors Don’t miss watching this webinar on how to quickly and easily deploy Spark, Hadoop, and more on AWS – without DevOps or AWS-specific skills.

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Hewlett Packard Enterprise (HPE) is transforming how enterprises deploy AI / Machine Learning (ML) and Big Data analytics. HPE’s container-based software platform makes it easier, faster, and more cost-effective for enterprises to innovate with AI / ML and Big Data technologies – either on-premises, in the public cloud, or in a hybrid architecture. With HPE, our customers can spin up containerized environments within minutes, providing their data scientists with on-demand access to the applications, data, and infrastructure they need.