F1 Dashboard Using PowerQuery

Harnessing Excel's web scraping, data transformation, and visualization capabilities

This passion project was solely created on Excel and received 292 likes and 17 comments when I shared it in a data analytics Facebook group! I was just starting out with business intelligence, so the feedback was very motivating.

ETL Process

PowerQuery was used not only for data transformation but also for web scraping, allowing for automated data extraction from online sources. It streamlined the Extract, Transform, Load process, handling tasks such as importing raw data from multiple sources, cleaning and reformatting it, and combining various datasets. Additionally, PowerQuery’s capabilities made it easy to perform advanced data manipulation and analysis, while Excel's design features were utilized to create intuitive visualizations and dashboards.

⁠

Dashboard

The dashboard has three main pages: Seasonal, Grand Prix and Teams, and Drivers. You may click each photo to enlarge. For better user experience, sheets with raw data and backend calculations were hidden. Hyperlinks allow for easy navigation similar to a website. Small notes also indicate if filters can handle single or multiple selections.

⁠

Recommendations

I'd like to show more comprehensive data such as: Grand Prix winners not just those in 1st place but also 2nd and 3rd place podium finishers. Although this is not present in the Races dataset, I can extract it from Drivers with 2 or 3 under the Positions column.

I also want to lessen the items under each category by classifying them in new ways. For example, teams are combinations of companies and car manufacturers which is why you'll see Red Bull Honda and Red Bull Renault, or Sauber Ford and Sauber Ferrari. I'll spend some time separating the two so they can have 2 filters instead of 1 with so many options.

I want to add a page that lets the user compare 2 or more drivers using all the stats currently on the Drivers page.

Want to print your doc?
This is not the way.

Try clicking the ⋯ next to your doc name or using a keyboard shortcut (

CtrlP

) instead.