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DSC Webinar Series: 7 Reasons to combine SPSS Statistics and R”

  • Sean Welch 

According to the Rexer survey,* R is the analytic software of choice for data scientists, business analysts, and data miners in the corporate world. Despite R’s popularity, adoption of R has lagged due to a few limitations like:

• Collaboration & Deployment – R makes sharing work among an analyst team difficult, especially when team members do not have the same level of R knowledge. Also, using R to integrate predictive outputs into an operational environment can be difficult.
• User Interface – R does not have a modern graphical user interface, which makes it difficult for those who are not R programmers to use it.
• Learning curve – R is not easy to learn for everyone. Not everyone is a programmer.
• Data Complexity – R does not easily connect to databases natively.
• Output – Production of publish-ready output is difficult.
• Performance & Scalability – R can very quickly consume all available memory.
• Enterprise security – The security of the packages that you download is not assured.

So if some of these challenges or limitations resonate with you, then join this webinar to really understand how you can overcome all these limitations by integrating R with IBM SPSS Statistics.

Jon K Peck, Senior Software Engineer, IBM SPSS
Murali Prakash, Product Marketing Manager, IBM

Hosted by:
Tim Matteson, Co-founder, Data Science Central