Get to know the Cloudera Data Platform (CDP)

Anthony Huinker, Cloud Sales Engineering Manager

CDP manages data in any environment, including multiple public clouds, bare metal, private cloud, and hybrid cloud. With Cloudera's Shared Data Experience (SDX), the security and governance capabilities in CDP, IT can confidently deliver secure analytics running against data anywhere. CDP is a new approach to enterprise data, anywhere from the Edge to AI.

Timothy Spann, Principal Field Engineer

Increasing the adoption of cloud native event driven applications creates new challenges for enterprises to acquire and distribute relevant data to the right applications in real-time. In this session, we will show you how Cloudera Data Flow’s streaming capabilities help enterprises to build end-to-end data pipelines in multi-cloud environments. You’ll see how easy it is to create fully secure NiFi and Kafka CDP Data Hub clusters and use them to build the backbone for your event driven applications and data movement needs in the cloud.    From logs to databases to messaging systems to events to files, Apache NiFi powers your real-time data ingest needs.

David Bao, Director of Product Management

Enterprise IT is overwhelmed trying to manage data security and governance across fragmented systems infrastructures. This impacts security and efficiency and also frustrates business users through a lack of agility and flexibility. Today you will see how Cloudera SDX not only provides the enterprise-grade security and governance IT needs but also seamlessly and consistently applies these policies across the complete analytics landscape. With SDX, IT has centralized data security, governance, and control it requires to safely and securely meet the ever-changing business needs.

Jonathan Hsieh, Director of Product Management, Data Management

Machine Learning (ML) and Artificial Intelligence (AI) are some of the fastest-growing investment areas within companies around the world. However, the vast majority of ML projects do not even make it out of the experimentation phase, let alone into production.

Cloudera Machine Learning (CML) is designed to tackle this problem by providing an end-to-end solution for the entire ML lifecycle. CML brings the agility and economics of cloud to self-service machine learning workflows with governed business data and tools that data science teams need, anywhere.

During this demo, you’ll learn how:

• Administrators can deploy ML workspaces for teams with secure access to data and tools for end-to-end data science workflows 

• Users get on-demand access to auto-scaling, auto-suspending compute resources and their preferred editors, tools and libraries, all within administrative guardrails for security and cost  

• Teams can collaborate to accelerate projects from data engineering and exploration to model training and experiment tracking, to deploying and managing models via interactive applications in production