Why Your Data Science Architecture Should Include a Data Virtualization Tool (New Zealand)

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Chris Day
Chris Day Director, APAC Sales Engineering Denodo

 2020/11/04

Presented at CDAO New Zealand

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, most architecture laid out to enable data scientists miss two key challenges:

  • Data scientists spend most of their time looking for the right data and massaging it into a usable format
  • Results and algorithms created by data scientists often stay out of the reach of regular data analysts and business users

Watch this session on-demand to understand how data virtualization offers an alternative to address these issues and can accelerate data acquisition and massaging. And a customer story on the use of Machine Learning with data virtualization.

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