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Comparing SAS/R/SPSS/Python for Data Science


Every analytic practitioner has a preference; but in this one hour webinar, you will see a comparison of different statistical programming languages/packages, specifically R/SAS/SPSS/Python.

On Nov 9, John Friedmann, Manager, Analytics at Deloitte 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.

John will also examine how data is stored and transformed within each framework including efficient coding tips, as well as some data visualization capabilities.

Gather your analytic team and see a few key packages for everyday use in R and Python as well. This is one webinar not to be missed!



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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