This course introduces the user of Spotfire to TIBCO Enterprise Runtime for R (TERR) and shows how scripts written in the R language can be used to extend Spotfire’s capabilities.

Spotfire Analyst includes TIBCO Enterprise Runtime for R (TERR). TERR gives you the power to extend Spotfire’s capabilities by using R scripts to perform data manipulation and data analysis tasks in Spotfire analyses. This course includes examples representing some of the most common applications of R scripting in Spotfire. The course also enables you with the general skills and knowledge required to apply your own R scripts in Spotfire. Spotfire version 6.5 or higher is required.

Note: This course does not include R language instruction. 

Audience: Power users and data scientists who want to use R scripts in Spotfire to extend their analyses with data manipulation and data analysis tasks powered by TIBCO Enterprise Runtime for R (TERR)
Course Duration: 4 days

Training and experience coding in the R language is recommended, but not required, before you take this course.

Students should also participate in Spotfire Analyst Essentials I and II before taking this course.

Course Outline:
  • Introduction to R and TERR
    • What is R? Why use R?
    • What is TERR? Why use TERR?
    • Differences between TERR and open source R
    • Learning the R language


  • Overview of TERR in Spotfire
    • Reasons for using TERR and Spotfire together
    • User roles for working with TERR and Spotfire
    • Ways to use TERR in Spotfire
    • TERR expression functions
    • TERR data functions
    • Using TERR in the different Spotfire clients


  • Architecture for TERR and Spotfire
    • TERR embedded in Spotfire Analyst and Spotfire Desktop
    • TIBCO Spotfire Statistics Services
    • Publishing analyses with TERR functions on Spotfire Web Player


  • Setting Up Your TERR-Spotfire Environment
    • Using the TERR console
    • Using TERR with RStudio
    • Installing packages from CRAN on TERR
    • Accessing TERR documentation and R package documentation
    • Installing open source R (optional)


  • TERR Expression Functions
    • Using in-line TERR expressions
    • Registering and using TERR expression functions
    • TERR expression function inputs
    • TERR expression function outputs
    • How TERR expression functions respond to filtering
    • Using TERR expression functions with trellised visualizations
    • TERR expressions warnings and errors Example: K-means clustering
    • Example: LOWESS smoothing
    • Example: Regression lines with confidence bands


  • TERR Data Functions
    • Creating TERR data functions
    • Running TERR data functions
    • Modifying TERR data functions
    • Data function input parameters
    • Data function output parameters
    • Data functions progress, warnings and errors
    • Troubleshooting TERR data functions
    • Other ways to insert data functions
    • Refreshing data functions with action controls
    • Example: K-means clustering
    • Example: Regression modeling
    • Example: Classification modeling