Diving Into Tableau


The idea behind this project was to learn visual communication through data visualization with Tableau. I am graduating in July 2022 with a Bachelor’s in Business Analytics and data visualization is a fundamental part of what I will be doing in the workforce. In preparation for my career, I decided to devote 12 weeks to learning Tableau and becoming competent in its use.

I knew from the outset that I would not be able to master Tableau in 3 months. Experts in this software are still discovering new ways of finding impactful insights through data manipulation and visualization. My goal was to create a strong foundational knowledge of how Tableau functions, be competent at a professional level with its use, and create projects to demonstrate my learning to both myself and to others.

I organized my project into checkpoints with Mini Projects due every few weeks. As I progressed through the project, I naturally created these projects to demonstrate the skills I was learning at the time.


I spent quite a bit of time performing research on what makes Tableau so powerful and why it has become one of the most prominent tools within business, alongside Excel. My findings included the fact that Tableau can work with Big Data and can handle much more rigorous levels of detail than Excel.

I used the exorbitant amount of content on YouTube, Tableau Help, and Playfair Data to aid my learning. I found explanations for basic Tableau problems, tutorials for specific-use dashboards, and help surrounding calculated fields. This process continued throughout the duration of my project. The knowledge and skills I learned with these resources are demonstrated in my Mini Projects.

For the purposes of my learning, I used the Sample Superstore dataset provided with the download of Tableau. Not only is this dataset used in almost every tutorial or instructional piece of content, but it is also directly related to what I will be doing when I begin working as a supply chain analyst for Walmart later this year. I completed two Mini Projects during the course of this project designed to demonstrate my learning and abilities within Tableau. While these projects do not represent the totality of my efforts or my learning, I feel they provide a good example of what I have achieved over the course of this project. Before this, I had never opened Tableau. Now, I feel confident representing data through interactive visualizations and summaries.

Mini Project 1: Regional Sales, Quantity, and Discount Breakdown


While it may appear simple at first glance, the dashboard above is very complex. Viewing this dashboard within Tableau allows you to interact with 100% of the data being displayed. All of the sections are connected and filtered by one another. If you select the East region in the Average Discount per Region tile, the entire dashboard will filter down to that region. This allows the user to have a broad overview of the performance of their stores but also the capability to drill down to really see which factors are contributing or being a detriment to that performance.

Because of my unfamiliarity with Tableau, it took a long time to figure out how to format the dashboard so it looked presentable. Unlike Excel or Google products, Tableau has an extremely complex formatting suite. Discovering which parameters or settings needed to be changed was more challenging than I originally expected. It felt similar to going from Microsoft Paint to Adobe Illustrator with the added complexity of coding/programming .

This dashboard is powerful in the hands of an analyst. The split of quantity, sales, and average discount percentage for each region allows them to instantly begin seeing trends, both positive and negative, that are affecting the performance of the company.

Example of the filtered dashboard

Mini Project 2: Shipping Breakdown and VIP Analysis

Maintaining a fast and accurate supply chain is essential to any retail business. During the process of completing some tutorials for my first mini project, I calculated the top five biggest spenders with this retail store. Using this filter, I started to breakdown the shipping methods being used.


The top half of the dashboard is broken down by sub-category of sale, the shipping mode used, and the quantity of items within that sub-category being shipped. I was interested in learning about how the VIP customers I had calculated earlier would fit into this chart. After I had determined products purchased in these large orders, I realized that an important metric was not being shown on my shipping dashboard, speed of shipping.

This challenge provided a great learning opportunity for me. I used skills I learned previously regarding calculated fields to program a filter and apply it to the VIP customers and their shipping information. I designed this worksheet to be a prototype that could be expanded to the rest of the dataset. The dashboard now allows the user to see when the products were ordered, when they were shipped, and if that shipping speed was ‘speedy’, ‘normal’, or ‘slow’ via the color code.


The biggest challenge I faced during my project was finding the correct teachers on the internet. Tableau has numerous tutorials on its website, but YouTube and online forums are also overflowing with knowledge. The breadth of this knowledge can be daunting and surprisingly difficult to sift through.

The second greatest challenge I faced during my project was learning how to use calculated fields and level-of-detail formulas to manipulate my visualizations.  This required a lot of patience and utilizing online resources to review and edit my calculations.


At the start of the project, I knew I would need to create my two mini projects and the worksheets included on these dashboards would need to be related and coherent. This led me to find tutorials that constructed dashboards related to retail sales. I would then attempt to build those same dashboards. After two or three tutorials, I felt confident to begin building a dashboard for my mini project. I repeated this process multiple times throughout my project.

There were times that my process above was not sufficient for the kind of dashboard I was trying to create. This led me to do more in-depth research within Tableau documentation and from the writings of Tableau Zen Master Ryan Sleeper. After this research I usually had a better idea of how to change my dashboard and my worksheets to really tell a story with the data.

Overview of Project Experience

Throughout my experience over these past few weeks, I have learned valuable new skills that are directly applicable to my career. Though learning Tableau by myself was a big challenge, I feel that I performed well and have a sufficient understanding to add value to a project today if I was asked to.

I would recommend that other young professionals take it upon themselves to explore the tools of their field, even if it daunting. I feel more confident in my ability to add value in any position now that I have begun my Tableau journey.

Key Insights

At the beginning of my project, I felt that I needed to make all of my visualizations colorful, interactive, and unique looking. The biggest insight I got into becoming a Tableau master is that simplicity is the best route. Even the most advanced Tableau users in the world still favor using bar graphs, line charts, and crosstab formatting. The key to becoming incredible at data visualization is not in creating new ways to view and interact with the data, it is communicating a clear and singular message, one insight at a time.

Video Summary

Project Write-Up