We are excited to announce a brand new district on the Alteryx Analytics Gallery, the Predictive District. This district is now available to the public and contains new tools, usage samples, and analytic apps designed to enhance the predictive analytics capabilities of Alteryx, and make advanced analytics more accessible to data analysts with easy apps and examples to quickly leverage some of the predictive tools within Alteryx. The Predictive District will continue to grow over time through a combination of new capabilities created by the Alteryx product team, and through contributions from the Alteryx user community.
To get things started, we are launching eight new predictive tools and five new usage samples in the Predictive District. The new tools introduce new advanced analytics methods which assist in model diagnostics and comparison, offer the ability to export models created in Alteryx to external scoring engines, and a tool that extracts estimated coefficients from models created using the Count, Gamma, Linear, and Logistic Regression tools into an Alteryx table (as opposed to a report element) that can be used as input into other Alteryx tools and calculations.
All of the tools within the Predictive District stem from customer feature requests, and several of them have been around for some time, having been created to address the needs of specific customers, but are useful to a broader set of users.
The new tools being released in the Predictive District include:
In addition to the tools, five samples are included in the initial wave of items in the Predictive District. The samples are:
This is the first wave in what will be an expanding set of predictive oriented tools, macros, and workflows. We already have a number of new tools in the works, and encourage others to join in adding to the expanding list of predictive analytic samples, workflows and apps in the Alteryx Gallery by making contributions to the Predictive District. We believe that using the Predictive District as a channel for distributing new Alteryx functionality will better allow us to provide users of all skill levels the functionality they need to address the analytical challenges they face, without overburdening their tool palettes, make predictive analytics more accessible, and reduce the need for advanced users to write their own custom R code in Alteryx since they can make use of new functionality in the Predictive District.
We encourage you to visit the new Predictive District and experience all of the new samples and tools available to you.
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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