Advanced Analytics and Machine Learning with Data Virtualization

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Presented by

Paul Moxon, VP Data Architecture & Chief Evangelist, Denodo

About this talk

Advanced data science techniques, like machine learning, have proven an extremely useful tool to derive valuable insights from existing data. Platforms like Spark, and complex libraries for R, Python and Scala put advanced techniques at the fingertips of the data scientists. However, these data scientists spent most of their time looking for the right data and massaging it into a usable format. Data virtualization offers a new alternative to address these issues in a more efficient and agile way. Attend this webinar and learn: How data virtualization can accelerate data acquisition and massaging, providing the data scientist with a powerful tool to complement their practice How popular tools from the data science ecosystem: Spark, Python, Zeppelin, Jupyter, etc. integrate with Denodo How you can use the Denodo Platform with large data volumes in an efficient way About the success Prologis has had as a result of operationalizing their Machine Learning analytics with data virtualization

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For IT professionals who are focused on data integration and enterprise data management and are overwhelmed by the growing number of data and data types, data virtualization provides real-time integration with agility to access and integrate disparate sources with ease. For business professionals, Data Virtualization brings agile information access that in turn drives business agility. The webcasts provided in this channel by Denodo, the leader in Data Virtualization, provide the latest in common usage patterns, use cases, best practices and strategies for driving business value with data virtualization.