[Webcast] Scalable Data Science with R - August 16th, 2016

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[Webcast] Scalable Data Science with R - August 16th, 2016

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Start Date:  Tuesday, August 16, 2016

Start Time:  10AM PT, San Francisco

1pm - New York | 6pm - London | 10:30pm - Mumbai |Wed, August 17th at 1am - Beijing|Wed, August 17th at 2am - Tokyo | Wed, August 17th at 3am - Sydney

Duration: Approximately 60 minutes

Cost: Free.


R is the fastest growing advanced analytics language with a vibrant community of data scientists, analysts, and researchers numbering in the millions who contribute thousands of packages to open source. But the data and processing limitations associated with R are real challenges. As real-world data grows exponentially, analysts find themselves wrestling with billions of records to analyze complex relationships to tackle new business problems.

Join Teradata Roger Fried, Senior Data Scientist and Brian Kreeger, Senior Data Scientist and local R User Group organizer, with over 30 collective years of experience designing and implementing big data analytic solutions in healthcare, finance and retail.

This webcast discussion will cover the following topics:

  • Understanding and building an architecture to scale R
  • Leveraging R data science libraries for business analytics
  • Converting and operationalizing an existing R script

Presented by: Brian Kreeger, Roger Fried

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brian-kreeger.jpgAbout Brian Kreeger, Senior Data Scientist – Teradata

Brian Kreeger is a Data Scientist with the Advanced Analytics Strategy and Adoption team, helping Teradata Aster's customers drive their Analytical Mission by providing guidance and education. Brian is a 20-year veteran of developing and implementing solutions to complex business problems, with experience in healthcare, finance and retail. He has a MA in Mathematics from Eastern New Mexico University.


About Roger Fried, Senior Data Scientist – Teradata

Roger is a Senior Data Scientist within Teradata Aster's Advanced Analytics Strategy & Adoption Team. He has an MBA in Finance from the University of Texas at Austin and is completing his Masters in Predictive Analytics from DePaul University. His primary role is to drive big data analytics adoption within some of Aster's customers.


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