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Cloudera Data Platform (CDP) supports everyone in the enterprise with multi-function analytics in a hybrid and multi-cloud environment. CDP uses Workload Experience Manager (Workload XM) to provide a complete view of what’s running across on-premises and cloud, millions of queries and hundreds of data sets. With Workload XM’s intelligent workload management, you easily maintain optimum performance and cost by keeping your clusters healthy and productive.

Cloudera Workload XM provides enhanced visibility and actionability to efficiently migrate, analyze, optimize, and scale workloads, on-premises and in any cloud. Users experience reduced migration risk, faster troubleshooting and root cause analysis, greater uptime, and higher resource utilization.

Hear from Raman Rajasekhar as he shares how using Cloudera Workload XM helps data administrators:

  • Proactively optimize workloads

  • Improve application performance

  • Balance infrastructure capacity for all stages in a data pipeline

This webinar will include a Workload XM demo, customer success stories, and Q&A with our panel of experts. We hope to see you there!




Director of Product Marketing, Data Warehouse

David Dichmann


David is responsible for product marketing for the Cloudera Data Warehouse. David has over 25 years experience in information architecture and enterprise architecture, turning data into information to help businesses and people make an informed decision. Before joining Cloudera, David has worked for companies like Sybase, SAP, and Hewlett Packard Enterprise. David has been published in industry magazines and is a regular speaker at industry events.

Product Manager, Cloudera Data Warehouse

Raman Rajasekhar


Raman specializes in building Machine Learning, Predictive Analytics, and Data Management products, and has a passion for creating and implementing high-performance algorithms for massively parallel processing (MPP) and Big Data platforms. Raman has over 15 years of international experience in R&D, product development, data science & machine learning, and engineering with a deep understanding of healthcare, financial and high-tech manufacturing domains.

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