in Blog

November 12, 2021

Using R for dashboarding vs. self-service BI


Edwin Lisowski

CSO & Co-Founder

Reading time:

6 minutes

When it comes to business intelligence and data visualization, you have two options. You can decide to build your own BI dashboard from scratch using one of the programming languages, or you can opt for self-service BI, where everything is initially encoded and configured, and all you have to do is to adjust the dashboard to your needs. Which solution should you choose?

At first, the answer seems obvious. After all, self-service BI allows you to save time, there is much less work involved, and you can start right away. That’s all true, but you have to remember that building your own business intelligence dashboard from scratch can give you more flexibility. You can adjust every single element to your needs so that everything works and looks precisely as you need.

So as always, it’s just a matter of your skills, resources, and requirements. The fewer skills/resources/requirements you have, the more probable it is you will pick the self-service BI option. However, for the sake of this article, let’s take a closer look at both these options.

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Building a dashboard in R

Why should you choose this language? There are a few reasons. For starters, R is an open-source programming language. There are almost no limitations to the way you use it and what for. Moreover, it’s accessible and compatible with many systems and platforms. Therefore, you can be sure that your R-based dashboard will work perfectly with your IT infrastructure and data sources.

R is, in general, perfect for data visualization purposes. It provides necessary objects, operators, and functions that enable you to model and visualize the data you have. Take a look at an exemplary dashboard made with the R language:

Building a dashboard in R


As you can see, everything is transparent and readable. That’s because this language is perfect for data science purposes. Many companies operating in this field use R to store and analyze data. It also works perfectly with statistical modeling, as it has many statistical and visual capabilities. At this point, it is vital to mention that data scientists frequently use R to run diverse types of data modeling, including classification and clustering.

There is one more reason why you should pick R for data visualization. It’s called the flexdashboard package. With this open-source package, you can build your own dashboards in R. Flexdashboard is based on R Markdown, which is a file format for making dynamic documents with R. When you have both these components, you can easily publish dashboards containing groups of related data visualizations. Flexdashboard is quite flexible, too! It comes with a whole range of additional components such as value boxes, text annotations, and grid graphics.

And on top of it all, R dashboards are adjusted to work with both desktop and mobile devices. All in all, R is a perfect tool for all of your data visualization and dashboarding purposes.

self-service BI


And now, let’s talk about our second possibility. Suppose you don’t want to code anything, and you’re looking for a ready-made solution. This is where self-service BI comes into play. What do you need to know about this option?

What do you need to know about self-service BI?

There are many ready-made BI tools available on the market. Some of the most popular ones are:

  • Microsoft Power BI
  • Tableau
  • Sisense
  • DOMO
  • SAP Analytics Cloud

The whole point of these applications is to provide users with BI capabilities without the need to code anything. Self-service BI allows non-tech users such as business analysts to run queries, generate reports, and create data visualizations without asking for programming support.

Generally speaking, all these self-service tools have intuitive interfaces so that they are relatively easy to use. The most advanced tools also have more complex options for the more tech-savvy users, but that’s not the main idea behind these programs.

tableau console


Read more about Business Intelligence Product: Which one to pick for your team?

Benefits and challenges of self-service BI

What are the benefits of self-service business intelligence? First off, everything is readily available. You don’t have to build anything or adjust your IT infrastructure. This way, your data team can focus on the most pressing issues instead of looking for the best technical solution. Secondly, there are no tech skills required to use these programs. Therefore, you can give access to your employees outside IT or data science departments, and they still should be able to master all the basics. With more users, you can get your job done more quickly, which is yet another significant benefit. And lastly, with these tools, you can introduce a data-driven approach to your whole organization, which in turn will help you gain a more competitive edge.

Of course, all of that doesn’t mean that this service is flawless. There are a few things that you have to keep in mind before you make a decision. For starters, you have to pay attention to possible incomplete data sets or errors within them. If they slip unnoticed, your self-service BI software will likely produce inaccurate or even incorrect results. For example, in many companies, users work with different versions of the same data sets, which can cause some problems.

Secondly, you have to think about data security issues. We have written a whole blog post about big data security. You ought to read it! One of the problems that come to mind is unauthorized access. With these ready-made BI platforms, some users could access your company’s sensitive data.

Obviously, you don’t want that to happen. Make sure you have all the safety measures in place.
The last thing that we have to mention is supervision. You have to be aware that self-service BI platforms can quickly become messy and chaotic if there is no supervision by the data science team. Make sure there is at least one person responsible for keeping everything under control.

So, what’s the answer to our initial question? Which option should you choose? As always, it depends. If you have the necessary skills and resources, and you have some non-standard requirements, you should build your own dashboard in R. If you’re just starting with business intelligence services or your data needs are relatively small, opt for the ready-made software.

And if you need any help with BI in your company–remember that the Addepto Team is always ready to help! Just go to the contact section and tell us something more about your data needs!


Business Intelligence