Recently Boris Evelson of Forrester Research raised some interesting question around the use and integration of R within the context of an overall BI/Analytic workflow and platform. For my short reply, visit his blogpost (and see my reply) here. In the meantime I wanted to take a moment to walk through how we at Alteryx are in the process of seamlessly integrating R into the Alteryx platform. For those of you who my not know, basic integration occurred with the introduction of the R-tool in the 7.0 release of Alteryx in February, which allowed R scripts to be created and run in an Alteryx workflow. Closer integration, along the lines consistent with your specific points, was one of the main objectives with our recent Alteryx 7.1 release where we added 18 new R tools to the platform.
Going forward, the level of integration between Alteryx and R will continue to increase. Some key points to note on the use and integration of R within the broader context of Alteryx:
Predictive and strategic analytics remain a major focus in our product roadmap with more tools, complete solution packages, and apps planned in our upcoming releases. If there is a feature you'd like to see in Alteryx, please send us an email at "Products at Alteryx.com."
Dr. Dan Putler is the Chief Scientist at Alteryx, where he is responsible for developing and implementing the product road map for predictive analytics. He has over 30 years of experience in developing predictive analytics models for companies and organizations that cover a large number of industry verticals, ranging from the performing arts to B2B financial services. He is co-author of the book, “Customer and Business Analytics: Applied Data Mining for Business Decision Making Using R”, which is published by Chapman and Hall/CRC Press. Prior to joining Alteryx, Dan was a professor of marketing and marketing research at the University of British Columbia's Sauder School of Business and Purdue University’s Krannert School of Management.
Dr. Dan Putler is the Chief Scientist at Alteryx, where he is responsible for developing and implementing the product road map for predictive analytics. He has over 30 years of experience in developing predictive analytics models for companies and organizations that cover a large number of industry verticals, ranging from the performing arts to B2B financial services. He is co-author of the book, “Customer and Business Analytics: Applied Data Mining for Business Decision Making Using R”, which is published by Chapman and Hall/CRC Press. Prior to joining Alteryx, Dan was a professor of marketing and marketing research at the University of British Columbia's Sauder School of Business and Purdue University’s Krannert School of Management.
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