An Introduction to R for System Administrators

Commonwealth Room

Half Day Afternoon
1:30 pm5:00 pm
LISA16: Engineering

Data analysis is not just about discovery, it’s about communication. Good communication tells stories. Savvy system administrators provide their management with the background needed to maintain operations, manage budgets, support users, and provide their coworkers with the insights needed to keep their systems solid.

The R programming language and ecosystem constitute a rich tool set for performing system analyses, for communicating the results and importance of those analyses, and for automating the process with reproducible and repeatable results. This brief introduction to R and its ecosystem will provide a walk along the mainline—coming up to speed on R, accessing data, analyzing data, and getting the message out.

This tutorial is designed to:

  • motivate you to pick up R
  • demonstrate useful techniques using R
  • illustrate ways to simplify your life by automating data analysis and reporting

In-class demonstrations will be augmented with hands-on opportunities during the workshop. Additional exercises and data sets that students can explore following the workshop will be provided. If you plan on working on the exercises, install R and (optionally) R Studio.

Who should attend: 

System administrators who are awash in operational data and want to do a more efficient job of understanding their data and communicating their findings. Facility with programming and knowledge of basic descriptive statistics is assumed. Prior knowledge of R is not required.

Take back to work: 
  • Acquaintance with R, R packages, and R Studio
  • Understanding where R fits into the system administrator’s tool set
  • Familiarity with basic R data-manipulation techniques
  • Motivation to learn or improve your R skills
  • Next steps in learning and mastering R
Topics include: 
  • Introduction to the R ecosystem
  • R as a language
  • Basic programming in R
  • The data analysis workflow
  • Reading and writing data from files and pipes
  • Data frames and data frame manipulations
  • Exploratory analysis
  • Using the ggplot2 package for graphing
  • Other useful R packages. 

Examples will be based on situations encountered during routine system operations.

Additional Materials: 
Presentation Type: