Today, there are multiple dashboarding tools available for showing off your data and helping you make the best analytical decisions. Out of all of the options, which one should you choose?
There are a lot of dashboard tools that allow you to visualize and present your data in different ways. Throughout my college career studying data science, I have had experience in Tableau and Power BI and have seen R Shiny used by many colleagues. I will be expanding on how each one is helpful and which one I prefer. Obviously, there will be bias because of my level of skill with each one, but I will keep an open mind.
Tableau offers amazing visualizations that are very interactive and easy to customize. In my years of data analytics, I have never found an easier way to annotate a graph than in Tableau. I am very impressed by their visual features and how easy it is to find the perfect visual for what you are trying to analyze.
Although their visuals are quite impressive, their ability to transform data is weak. You will definitely need to do some ETL processing before loading your data into Tableau. Their options are somewhat limited to making simple changes to your data like the data structure.
Working Tableau, little to no coding experience is necessary. You can manage each visual with aggregations by point, click, and drag; however, having knowledge to code will help you bring out more insightful visuals by properly aggregating the data in ways that are might not be possible with the base commands.
Tableau’s ability to present data and findings is useful. In Tableau, you can create reports to combine to create a dashboard, which you can use to create stories. Their ‘story’ feature allows you to create slides that slowly walk the viewer through your data analysis. You can click and highlight specific data that you want the viewer to focus on.
Tableau requires that an individual user pays $70/month to create Tableau dashboards. To explore and play with trusted data in Tableau, you are looking at paying $35/month. For those who are only interested in interacting with an already created dashbaord, the price is $12/month. This is pretty expensive considering how many other tools give similar benefits at a lower price.
The visuals in Power BI are more limited compared to Tableau, however because Power BI is a very new application, features are being added to it every month. Their is even a Power BI community where you can suggest features you might find useful and then others can vote on them. The feature with the most votes will be sent to the top of the list to be implemented. There is also the visualization market place within Power BI that allows you to import visuals that others have created. You are not going to get the same flow as you would with Tableau as far as visual flexibility goes, but I have always been able to create what I needed.
Power BI makes up for everything it lacks with all of the data munging capabilities that it comes with. Not only can you do pretty much anything you need to whether it be aggregation, summaries, grouping, data structure, appending, merging, cleaning, etc., but you can also model your data to create relationships between all of your tables. Tableau does have this capability, but I find that Power BI gives me more control over how I want to connect each table. For the most part, you can figure out how to transform the data however you need it in Power BI. I think it is important to also add that any script you need to run in Python or R to get the data necessary can be ran in Power BI. This also works with visuals.
Like Tableau, you can get away with most of what you need done without coding; however, knowledge of coding comes very handy in Power BI. Power BI creates all of it’s tables using M code. Knowing how to Utilize this skill will help you create conditional columns and tables that are very difficult to create with the point and clicks. Power BI also uses DAX outside of the data transform tool. You can use DAX to create quick solutions to see calculations in new columns. This can be very useful and scales quickly instead of having to reload that column each time you investigate the data and run commands across the table.
Unlike Tableau, I wouldn’t say that Power BI is much of a presentation tool as it is an investigatory tool. Power BI allows you to shape the dashboard however you choose so that you come back and use it as an automated reporting system every time the data is updated. In my experience building Power BI reports, I usually create visuals and show a table with select filters so that those who are interested can open the report at any time and see their new numbers.
Power BI Desktop is free to use for anyone. You download it straight from the Microsoft app store and can use it to create any report you need.Although, in order to share that report, you will need to purchase Power BI Pro at around $10/month. Anyone who is given permission and has Power BI Pro will be able to see your published dashboards. Compared to Tableau’s prices, $10/month is a very low price for the amount of equipment you are getting.
Because R Shiny is created using R, you have all of the advantages that come with R. Ggplot2 is one of the greatest visualization libraries that I have ever used, so creating a dashboard with stunning visuals is more than capable in your Shiny app.
When cleaning your data, you will have the entire tidyverse backing you up, which is regularly updated to give you a fantastic data wrangling experience.
In order to create an R Shiny app, you will have to know how to code. R is a programming language. This may seem disappointing to those who have no coding experience; however, you can accomplish considerably more functionality than any of the other dashboards because it is completely coded.
Shiny apps are very flexible to however you want to design them. Because they are a web application, you can add whatever functionality you are able to code. This allows your UX to surpass those of Tableau and Power BI.
The R programming language is open source and can be downloaded on any platform. To host a shiny app, it is free with restrictions. You can make monthly payments to increase how many applications you can have, how many hours your apps can be used, etc.
My dashboard tool of choice is Power BI. Power BI connects easily to almost any data location. It is very convenient to use when I don’t have a lot of time because I can quickly connect data to it and start throwing things together just to explore what I am looking for. Then if I need to add any equations to see beyond what the data has, I just create a few quick measures to calculate for me. I have never had to put together a presentation, and I like to create dashboards for myself to track my own data, so a simple dashboard without the Tableau story feature is good enough for me.
I use Windows instead of Mac or Linux, so Power BI is available for me to use. Unfortunately, Power BI can only be downloaded from the Microsoft store and isn’t downloadable on other operating systems. If I were to switch to a different operating system, I would need to choose a different tool.
I would suggest trying out the free options and then use up the free trials on the expensive applications to get an idea of what applications suit you the best.
For attribution, please cite this work as
Sant (2021, April 7). Data Science with Keaton: Choosing The Right Dashboarding Tool. Retrieved from https://keatonjsant.github.io/posts/2021-04-07-dashboard/
BibTeX citation
@misc{sant2021choosing,
author = {Sant, Keaton},
title = {Data Science with Keaton: Choosing The Right Dashboarding Tool},
url = {https://keatonjsant.github.io/posts/2021-04-07-dashboard/},
year = {2021}
}