Ask the Expert Webinar Series

SAS® Viya® and R Integration

On-Demand • Cost: Complimentary

About the webinar

The SAS Viya platform is language-agnostic.

The SWAT package enables R users to interface from the client with Viya in-memory data tables and submit high-performance cloud-native algorithms to efficiently scale analytics from any integrated development environment.

This allows R users to embrace high-performance SAS Analytics without a full dive into the SAS programming language, empowering both open source and SAS users to collaborate on a single analytics platform.

This session is open to all skill levels who are interested in how R integrates with Viya. However, some experience working with R is beneficial.

You will learn:

  • About the SWAT package and how it enables open source integration with Viya.
  • How to submit CAS actions using R to run in-memory analytics.
  • The general integration aspects of loading data into memory, analyzing distributed tables, creating predictive models, and downloading results to the client using R functionality.
  • How to integrate R into Model Studio, SAS/IML® and SAS® Enterprise Miner™.

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About the Expert


Jordan Bakerman
Senior Data Scientist, SAS

Jordan Bakerman is a Sr. Data Scientist for the Financial Services Business Unit at SAS, where he is responsible for creating and delivering open source content. Before his current role, Bakerman worked in the Education Division, creating multiple full-length training courses. Bakerman developed the SAS®9 Programming for R Users course, the R and Python Open Source Integration course for SAS Viya and the SAS Reinforcement Learning course. Bakerman also contributed to the deep learning course. He has developed training content for both the SAS e-learning and Coursera platforms. In addition to creating open source content, he has consulted with SAS clients to build and deliver AI solutions with SAS Viya. Before joining SAS, Bakerman was at North Carolina State University, where he completed his PhD in statistics. His dissertation focused on leveraging open source social media data to solve real-world problems. He worked on geotag imputation and dynamic variable selection to forecast civil unrest in South America.

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