Details
Together, Tableau and R offer accessible analytics by allowing a combination of easy-to-use data visualization along with industry-standard, robust statistical computation. Readers will come across a wide range of machine learning algorithms and learn how descriptive, prescriptive, predictive, and visually appealing analytical solutions can be designed with R and Tableau.
In order to maximize learning, hands-on examples will ease the transition from being a data-savvy user to a data analyst using sound statistical tools to perform advanced analytics.
Outline
» Make R function calls in Tableau, visualizing R functions with Tableau using RServe.
» Use the CRISP-DM methodology to create a roadmap for analytics investigations.
» Implement various supervised and unsupervised learning algorithms in R that return values to Tableau.
» Get to grips with advanced calculations in R and Tableau for analytics and prediction with the help of use cases and hands-on examples.
» Make quick, cogent, and data-driven decisions for your business using advanced analytical techniques such as forecasting, predictions, association rules, clustering, classification, and other advanced Tableau R calculated field functions.
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