Minimizing the Complexities of Machine Learning with Data Virtualization

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 McCormick has had as a result of seasoning the Machine Learning and Blockchain Landscape with data virtualization