PowerBI vs. R Shiny: Two Popular Excel Alternatives Compared

PowerBI vs. R Shiny: Two Popular Excel Alternatives Compared

PowerBI vs. R Shiny: Two Popular Excel Alternatives Compared. How does R Shiny compare to drag and drop visualization tools like PowerBI?

Choosing the appropriate dashboarding/reporting/BI tool has never harder than it is now, as there are plenty of genuinely great options such as R Shiny, PowerBI, and Tableau. Today we’ll compare two widely used tools at Fortune 500 companies:

  • PowerBI — a collection of software services, apps, and connectors that work together to turn unrelated sources into coherent, visually immersive, and interactive insights (_source: [Microsoft_](https://docs.microsoft.com/en-us/power-bi/fundamentals/power-bi-overview))
  • R Shiny — a web framework written in R, widely used to make dashboards and interactive web applications

One thing to keep in mind: R Shiny is not a reporting/dashboarding tool. Rather, it is a full web framework. As most people use it to make dashboards, and many of our customers compare R Shiny with PowerBI when they invest in analytical solutions, we can consider this comparison fair. We’ll start with a basic overview of PowerBI and then compare both tools in various areas, such as:

  • Connectivity
  • Chart Types
  • Ease of Use: Simple Charts
  • Ease of Use: Simple Dashboards
  • User Input and Interactivity
  • Visual styling
  • Conclusion

PowerBI Overview

As mentioned previously, PowerBI is used to represent interactive insights from various data sources visually. It is a perfect tool for reporting, which is a read-only operation and is relatively easy to build and maintain.

PowerBI is also one of the easiest tools to get started with, as only a couple of crash courses should get you up to speed in no time. We’re not saying R is difficult to learn, but the drag and drop GUI interface is considered to be easier to learn than R, at least for business folks.

But here’s one of the most important selling points — PowerBI just looks good out of the box. You don’t have to be an expert to produce great-looking visualizations with PowerBI. Shiny requires much more manual labor to produce great-looking dashboards. Manual work isn’t necessarily bad, as there’s no limit to what you can do if you’re willing to put the effort in, but simple drag and drop tools are more than enough most of the time.

For every pro, there’s a con, and PowerBI is not an exception. One of the most significant disadvantages of PowerBI is that it is** read-only.** As a user, you cannot use charts/tables to make decisions and save them in a database directly.

Also, PowerBI doesn’t have an accessible source code.You can only edit fields in WYSIWYG mode, which makes PowerBI easy to start but difficult to maintain. Having no source code makes it nearly impossible to have proper version control, automatically test logic, or collaborate on large projects.

power-bi r towards-data-science data-science r-shiny

Bootstrap 5 Complete Course with Examples

Bootstrap 5 Tutorial - Bootstrap 5 Crash Course for Beginners

Nest.JS Tutorial for Beginners

Hello Vue 3: A First Look at Vue 3 and the Composition API

Building a simple Applications with Vue 3

Deno Crash Course: Explore Deno and Create a full REST API with Deno

How to Build a Real-time Chat App with Deno and WebSockets

Convert HTML to Markdown Online

HTML entity encoder decoder Online

Power Query tips for every Power BI Developer

Use these simple yet powerful techniques to speed-up your Power BI development. If someone asks you to define the Power Query, what should you say?

Explore your JIRA Data with Power BI

JIRA Software provides bug tracking, issue tracking, and project management capabilities for teams and organizations. The JIRA content pack for Power BI helps you quickly import JIRA data so you can get an instant dashboard to analyze workloads...

Managing your Data with Microsoft’s Power BI

In a world where the sheer amount of data is often overwhelming, the ability to interrogate and organise data to make meaningful business decisions is more important than ever. Microsoft have created Power BI to enable every day users to use the...

Tableau vs Power BI: Comparing the Data Visualization Tools

In analytics, Tableau is the leading visualisation tool. Its rich analytical features and attention to data details are the reason behind its popularity. Power BI, on the other hand, is preferred by professionals who are more comfortable with...

Data Cleaning in R for Data Science

A data scientist/analyst in the making needs to format and clean data before being able to perform any kind of exploratory data analysis.