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For enterprise organizations, building robust data pipelines has become increasingly resource-intensive. Modern data engineering requires more advanced data lifecycle integration for streamlining security, governance, and maintaining data quality to enable advanced analytics and machine learning at scale. To tackle these challenges, enterprise organizations need a comprehensive and integrated data engineering experience for data pipeline preparation and management. 

  • Learn how Cloudera enables streamlined scheduling and workflow orchestration with Apache Airflow for analytical services such as Data Warehousing and Machine Learning using Spark

  • Experience visual, self-service troubleshooting and complete monitoring service for identifying and solving issues quickly

  • Explore how the Cloudera Shared Data Experience breaks down data silos and enables enterprise-grade security, governance and lineage tracking for data workflows



Senior Manager, Product Marketing MLOps

Santiago Giraldo


Santiago leads product marketing for Cloudera’s production machine learning products. With over 10 years in the data science and analytics software industry, Santiago focuses on enabling businesses to solve complex challenges with novel data strategies and machine learning approaches.

Senior Manager, Product Management, Data Engineering

Shaun Ahmadian


As Senior Product Manager, Shaun leads Cloudera’s data engineering and visualization products. Prior to Cloudera, Shaun was a lead solutions engineer for Arcadia Data, a big data business intelligence company enabling Fortune 500 enterprises with visual analytics and BI capabilities at scale.

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