Introduction
On day 2 of the dashboard week, we focused on the Olympics; this is the dataset used for the next cohort data schooler’s final interview. I’m picking the marathon in the Olympics over history. The original data doesn’t include event result; therefore, to finish this project, I have to find the supplementary data from the Olympics official website that obtain all results for each event. That allows me to do a time series analysis.
Data Manipulation
As I mentioned early, download the data from the Olympics, so the way to solve this is by creating a batch macro in Alteryx and scraping data from the Olympics website. The macro workflow is as shown below. Let’s look at the Alteryx workflow; it’s much cleaner than yesterday one, and it’s simple; the original data is also ok. I have to mention the name of all athletes because it doesn’t match the name on the Olympics website. However, this is an opportunity to use the fuzzy match tool for solving your problem. If you join two datasets directly, it won’t give you any outcome; nothing is in the inner join; instead, using the fuzzy match tool will return over 1000 players. So let’s get data from this. Once data manipulation finished, it’s time to design the dashboard, and thinking about how to build a dashboard, I used three bar charts in yesterday’s viz, so I might try differently today.
Dashboard Building & Designing
Once data manipulation finish, it’s the time to design the dashboard, and thinking how to build a dashboard, I used three bar chart in yesterday’s viz, so I’m going to try in a different way to visualise this topic.
I finished all charts by early afternoon; after that, I spent some time designing and finding insights from the dashboard. The final viz is here.
