Excel to Tableau

Mini skill case study.

MINI SKILL STUDYEXCELDATA VISUALISATIONTABLEAU PUBLIC

Fynn Burgess

11/22/20232 min read

turned on monitoring screen
turned on monitoring screen

Excel to Tableau

Please be aware that this dataset was created using AI and may not faithfully replicate real-world situations. While it can be utilized for learning purposes, the outcomes derived from it might not align logically or consistently with real-world scenarios. Exercise caution when drawing conclusions or making decisions based on this dataset, as its AI-generated nature could result in data patterns or conclusions that might not align with practical or logical expectations.

This dataset was taken from my mini skills case study available here:

https://fynnburgess.com/working-in-excel

About the dataset:

The dataset contains detailed information on various vehicles, encompassing different manufacturers, models, manufacturing years, vehicle types, prices in Australian dollars (AUD), available stock counts, and yearly sales figures for the year 2022.

Each entry in the dataset includes the following attributes:

· Vehicle ID: A unique identifier for each vehicle.

· Manufacturer: The brand or company producing the vehicle.

· Model: The specific name or model of the vehicle.

· Manufacturer, Model: A combined field indicating both the manufacturer and model.

· Year: The manufacturing year of the vehicle.

· Type: Categorization of the vehicle type, such as Sedan, Hatchback, SUV, Pickup, Coupe, Minivan, Wagon, Van, Convertible, or Minivan.

· Price (AUD): The price of the vehicle in Australian dollars.

· Stock Available: The count of available units in stock.

· Yearly Sales (2022): The number of units sold in the year 2022.

This dataset encompasses a range of vehicles, offering insights into the used dealerships’ diversity, pricing trends, and sales performance for different manufacturers, models, and vehicle types. It's structured to facilitate analysis and exploration of the automotive market landscape for various purposes such as stock research, pricing strategy, or sales performance evaluation. However, it's essential to note that as an AI-generated dataset.

Deciding between Excel and Tableau Public for dashboard creation depends on the knowledge and complexity of the project and user. Excel, a familiar spreadsheet tool, offers basic dashboard creation but often when looking for creative freedom in your dashboards you might run into limitations, as well as with handling large datasets. In contrast, Tableau Public excels in user-friendliness, handling complex datasets, and creating highly interactive, visually appealing dashboards. Its intuitive interface and large range of visualization capabilities make it suitable if you’re looking for advanced interactivity without a large amount of technical knowledge. Ultimately, the choice comes down to the project's complexity, dataset size, and the user's knowledge; Excel suits basic visualizations, while Tableau Public empowers users to craft more creative and interactive dashboards.

Things I learned:

1. Tableau scatterplots. I’ve never created them before, but it was made easy by Tableau’s Visualisation recommendations.

2. Learning to adapt to different software. This is enhanced due to working with the same dataset, creating a similar dashboard in Excel.

3. Tableau public desktop. Up until now, I have been using Tableau public web authoring. However, I found PC performance improvements by using the desktop version. Especially when the PC’s ram is already under high usage.

Tableau dashboard link

Like what you see?

Let's talk
fynn@fynnburgess.com