Tableau and R for Analytics Projects (2019)
2h 28mIntermediate2019-11-12
Authors
Curt Frye
President of Technology and Society, Incorporated
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
Importing data
Creating calculations in R
Creating and visualizing linear regression models
Detecting and visualizing outliers
Defining and visualizing clustering models
Creating a logistic regression model in R
Creating a support vector machine model
Visualizing random forest analysis data in Tableau
Learning objectives
Importing data
Creating calculations in R
Creating and visualizing linear regression models
Detecting and visualizing outliers
Defining and visualizing clustering models
Creating a logistic regression model in R
Creating a support vector machine model
Visualizing random forest analysis data in Tableau
Skills covered
RStudioTableauTableau SoftwareRStatisticsData VisualizationBusiness AnalyticsPersonaData AnalysisProgramming LanguagesData ScienceBusiness Analysis and StrategyBusiness Software and ToolsOpen SourceSoftware Development
Concepts
Introduction
- Include R analyses in your Tableau visualizations
- What you should know
Introducing Tableau and R
- Compare the strengths of Tableau and R
- See how R and Tableau can work together
- Install R on a computer
- Download and install CRAN packages in R
- Run Rserve and establish a connection to Tableau
Prepare for Analysis with 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
Create and Visualize Linear Regression Models
- Linear regression and multiple regression models
- Create a single- and multiple-variable linear regression model in R
- Analyze regression variables for significance in R
- Visualize data for linear regression in Tableau
- Add an R regression model to a Tableau viz
Detect and Visualize Outliers
- Explore outliers and outlier detection
- Create an outlier detection model in R
- Visualize data for outlier detection in Tableau
- Add an R outlier detection model to a Tableau viz
Define and Visualize Clustering Models
- Explore clustering algorithms
- Create a centroid-based clustering model in R
- Visualize clustered data in Tableau
- Add an R clustering model to a Tableau viz
Classify Data Using Logistic Regression
- Explore logistic regression algorithms
- Create a logistic regression model in R
- Visualize data for logistic regression in Tableau
- Add an R logistic regression model to a Tableau viz
Classify Data Using Support Vector Machines
- Explore support vector machine algorithms
- Create a support vector machine model in R
- Visualize support vector machine data in Tableau
- Add an R support vector machine model to a Tableau viz
Visualize Random Forest Analysis Data in Tableau
- Explore random forest analysis
- Create a random forest analysis model in R
- Visualize data for random forest analysis in Tableau
- Add a random forest analysis model to a Tableau viz
Conclusion
- Next steps