Description

Introduction

In a world flooded with data, the ability to communicate insights visually and interactively is a key skill for data professionals. This course, “Interactive Dashboards in R Using Shiny and Flexdashboard,” empowers you to turn raw data and statistical analysis into engaging, easy-to-use dashboards. With Flexdashboard, you’ll learn to create structured, multi-panel layouts with minimal code using R Markdown. Then, using Shiny, you’ll integrate real-time interactivity—allowing users to filter, explore, and interact with data live in a web browser. This combined approach is ideal for analysts, data scientists, and business intelligence teams who want to share results without needing traditional web development expertise. Whether you are building dashboards for internal reporting, performance monitoring, or public data storytelling, this course provides you with the tools and best practices to do it effectively, quickly, and professionally.

Prerequisites

• Working knowledge of R programming

• Experience with data manipulation (dplyr, tidyverse)

• Familiarity with basic data visualization in R (ggplot2)

• Some exposure to R Markdown (helpful but not mandatory)

• No prior Shiny or Flexdashboard experience required

Table of Contents

1. Introduction to Dashboarding in R
1.1 Why Dashboards? Use Cases and Benefits
1.2 Overview: Shiny vs. Flexdashboard vs. R Markdown
1.3 Installing Packages and Setting Up the Environment
2. Creating Static Dashboards with Flexdashboard
2.1 Layout Basics: Rows, Columns, and Pages
2.2 Adding Visuals: Charts, Tables, and Text Blocks
2.3 Formatting with Themes and Custom Styles
2.4 Using R Markdown to Build Standalone Reports
3. Adding Interactivity with Shiny
3.1 Embedding Shiny Components in Flexdashboard
3.2 Creating Inputs: Selectors, Sliders, Checkboxes
3.3 Making Content Reactive with render*() Functions
3.4 Building Dynamic Dashboards in One File
4. Visualizing Data
4.1 Building Interactive Charts with ggplot2 and plotly
4.2 Data Tables with Search and Filter (DT package)
4.3 Displaying Key Metrics and Value Boxes
4.4 Visual Best Practices for Dashboard Readability
5. Working with Real-World Data
5.1 Loading Data from CSV, Excel, and Databases
5.2 Connecting to APIs for Live Data
5.3 Filtering, Aggregating, and Transforming Data on the Fly
5.4 Caching Strategies for Large Datasets
6. Advanced Dashboard Features
6.1 Tabsets, Navigation Bars, and Multi-Page Layouts
6.2 Conditional Panels and Dynamic UI
6.3 Using reactive(), observe(), and eventReactive()
6.4 Custom JavaScript and CSS Enhancements
7. Deployment and Sharing
7.1 Publishing to shinyapps.io
7.2 Hosting on Shiny Server and RStudio Connect
7.3 Exporting Dashboards as HTML Files
7.4 Access Control and Authentication Options
8. Dashboard Design Principles
8.1 Designing for Usability and User Experience
8.2 Optimizing Load Times and Performance
8.3 Accessibility and Mobile Responsiveness
8.4 Gathering User Feedback and Iterating
9. Real-World Projects
9.1 Sales & Revenue Monitoring Dashboard
9.2 Public Health Data Dashboard
9.3 Interactive Data Storytelling Dashboard
9.4 KPI and Executive Reporting Dashboard
10. Templates, Resources, and Next Steps
10.1 Reusable Layout Templates
10.2 Helpful Packages and Shiny Add-ons
10.3 Debugging and Performance Tools
10.4 Learning Resources for Further Growth

This course equips you with the ability to create powerful dashboards that combine the elegance of Flexdashboard with the interactivity of Shiny. By the end, you’ll be able to build and share responsive, data-rich web applications that transform how others explore and act on your analyses—making your insights not just seen, but understood.