Reporting and Dashboarding using R (RRD)

Description and Training course goals:

R is an open-source programming language which has been extensively used in statistics, visualization, and data mining.

The goal of this introductory course is to enable participants to create reports and dashboards using R. Course participants will learn how to use the packages R Markdown and Shiny. Many exercises will help deepen the knowledge conveyed during the course and the participants will get the chance to create their own first reports and dashboards.

Target audience:

This course is aimed at all users who would like to use R for creating automated reports and dashboards.

Course Syllabus:

The course starts with a short introduction to RStudio's features regarding reporting and dashboarding. This is followed by introducing the syntax of R Markdown and Shiny. Participants will then get many chances to explore the new features in guided excercises during which they can create their own reports and dashboards.

In specific, the following topics will be covered:

  • Creating reports using R Markdown
    • Creating R Markdown files using RStudio
    • File format options (Websites, PDF, Word)
    • LaTeX notation
    • Graphic options (size, labels, numbering, title)
    • Visualization packages (ggplot2, plotly)
    • Formatting
  • Creating dashboards using Shiny:
    • Syntax (input, output, server, reactivity)
    • Creating interfaces (buttons, drop-down menus, etc.)
    • Reading, modifying, and exporting data
    • Displaying reactive tables, texts, and graphics in the dashboard
    • Creating von ETL-pipelines (Extract, Transform, Load) in the dashboard
    • Dynamic visualization of Data in the dashboard
    • Using plotting packages for dashboarding (ggplot2, plotly)

The complete course is taught in an interactive way to enable the participants to explore the various mehtods and procedures right away. Furthermore, every section will be followed by a set of excercises. The course is completely documented; this makes taking notes during the course obsolete and enables participants to fully focus on practicing the methods in R.

Course Requirements:

For this intermediary course, good knowledge of using R for data science is required. In specific, participants must be familiar with the tidyverse package.

Preparatory courses:

Our introductory course "introduction to Data Science using R (RE)" offers all the basics that are required for this course.

Supplementary courses:

Further R courses are currently being developed, which will cover the following topics: "advanced visualization in R", "introduction to statistics using R", "advanced statistics using R", and "Machine Learning using R".

Furthermore, we offer a series of methodological courses, which cover different software independent topics, for example methodological courses as “Efficient Data Management” (EDM), “Big Data Analytics” (BDA), “Decision Trees” (TRM), as well as “Methods of Statistical Data Mining” (MDM) and “Data Mining in Practice” (PDM).

Duration: 2 Days             Time: 9:30 - 17:00 h            Price: EUR 1.040,- (plus VAT) per participant



back to overview