Anaconda

Data Science for Big Data with Anaconda Enterprise

Let Anaconda Take Your Organization to the Next Level
Getting Python and R’s most popular data science libraries to work on a computational cluster can be a major challenge. And in a Big Data world, surmounting this challenge is key to leveraging data science within your organization to make smart, data-driven decisions.
In this webinar from Team Anaconda, we demonstrate how easily the Anaconda Enterprise data science platform integrates with Hadoop or Spark clusters, giving your data scientists access to the libraries they need and empowering you to extract the most value from your Big Data. The webinar is intended for IT managers and experienced Python and R users interested in writing code on Hadoop/Spark clusters.
You'll learn how Anaconda Enterprise:
  • Enables runtime distribution for Hadoop and Spark jobs
  • Gathers data from disparate sources for analysis
  • Easily connects to your Spark clusters and queries data from Hadoop
  • Features distributed computing with Dask
  • Deploys your Big Data applications

Meet Our Speakers

  • Daniel Rodriguez is a Data Scientist and Software Developer with over five years’ experience in areas ranging from DevOps to machine learning. He has performed data analysis and data engineering in big data environments across various industries.

    Daniel holds a degree in Electrical Engineering from Universidad de los Andes Colombia and an MS in Science in IT Management from UT Dallas. He is passionate about open source data technologies and has spoken at PyData and Spark Summit.
  • Gus Cavanaugh is a Product Marketing Manager at Anaconda, where he focuses on translating technical capabilities into user benefits. He has over five years’ experience in analytics and consulting for enterprises. Prior to joining Anaconda, he worked on projects ranging from small-scale data apps and dashboards to distributed Hadoop clusters at companies including IBM and Booz Allen Hamilton.

    Gus holds an MS in Systems Engineering from George Washington University and a BS in Business Administration from Washington & Lee University. He is a frequent speaker on analytics topics for non-technical audiences.

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