Tableau and R for Analytics Projects

Course details

On its own, Tableau is a powerful tool that helps professionals analyze, display, and generally make sense of the data at their fingertips. With the addition of R—a free, open-source language for data science—you can glean even more insights from your data. In this course, learn how to combine the analytical strengths of R with the visualization power of Tableau to analyze and present data more effectively. Instructor Curt Frye demonstrates how to install R and RServe; create a connection between Tableau and R; perform several types of analyses in R, from linear regression to cluster identification; and incorporate those analyses into Tableau visualizations.

Learning objectives
Configure and establish a functional connection between R and Tableau by installing R, RServe, and necessary CRAN packages, then successfully connecting both platforms to enable integrated analytics workflows.
Construct multiple types of predictive models in R including linear regression, logistic regression, and clustering algorithms, then integrate these models into Tableau visualizations for business decision-making.
Evaluate and interpret complex data patterns using advanced R algorithms (support vector machines and random forests) and assess model performance to determine the most appropriate analytical approach for specific business scenarios.
Design comprehensive analytics solutions that leverage the complementary strengths of both R and Tableau, creating end-to-end workflows from data import through advanced analysis to compelling visualization and presentation.

Concepts

Introduction

Gain valuable insights using Tableau and R

Introducing Tableau and R

Compare the strengths of Tableau and R
How Tableau and R can work together
Install R on a computer
Download and install CRAN packages in R
Run RServe and establish a connection to Tableau

Preparing for Analysis Using Tableau and R

Import data into R
Create calculations in R
Import data into Tableau
Create a visualization in Tableau
Create a calculated field in Tableau

Creating and Visualizing Linear Regression Models

Describe linear regression and multiple regression models
Create single- and multiple-variable linear regression models
Analyze regression variables for significance
Visualize data for linear regression in Tableau
Add an R regression model to a Tableau viz

Classifying Data Using Logistic Regression

Describe logistic regression algorithms
Create a logistic regression model
Visualize data for logistic regression in Tableau
Add an R logistic regression model to a Tableau viz

Classifying Data Using Support Vector Machines

Describe support vector machine algorithms
Create a support vector machine model
Visualize support vector machine data in Tableau
Add an R support vector machine model to a Tableau viz

Grouping Data Using Cluster Analysis

Describe cluster analysis
Do cluster analysis in R
Troubleshoot cluster analysis in Tableau
Write cluster data to a CSV file for use in Tableau

Classifying Data Using Random Forests

Describe random forest analysis
Create a random forest analysis model in R
Visualize data for random forest analysis in Tableau

Conclusion

Further resources