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Comparing SAS/R/SPSS/Python for Data Science

November 9, 2017
1:00pm - 2:00pm EST


This one hour webinar will compare different statistical programming languages/packages, specifically R/SAS/SPSS/Python. It will examine and contrast these languages and packages along a number of useful dimensions including:

  • ease of use
  • suitability for beginning analytics practitioners
  • popularity in the data science community
  • memory consumption and scalability
  • data storage and interoperability with large data stores such as Hadoop
  • extensibility
  • ability to perform complex machine learning and deep learning methodologies.

It will also examine how data is stored and transformed within each framework, efficient coding tips, as well as some data visualization capabilities. We will look at a few key packages for everyday use in R and Python as well.


John Friedmann

Manager, Analytics

John Friedmann has over 30 years of experience in advanced analytics. He specializes in advanced topics such as discrete choice modeling, market basket analysis, direct marketing analytics, media mix and channel attribution. Prior work includes advertising, telecom and pharmaceutical DTC analytics.

Knowledgeable in SAS, SPSS, R, machine learning and advanced statistical programming techniques.

M.A. Economics from Northwestern University

Brought to you by:

  • DMA Analytics Community. DMA members who sign-up for this webinar will automatically be included in the this community to stay informed of future calls.

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