Day 2 done! Today was not easy … The task sounded interesting though! The SFO Museum has been updating information of each flight going in and out of San Francisco Airport over the years.

The goal was to use this data to create a KPI dashboard and the only requirement was for it to have a Mapbox map in it. Sounds easy enough, so I started by having a look at the data to try decide what exactly I wanted to show in my dashboard.

Data Preparation

Overall, there was too much information to load it all into Alteryx, get it together and make a dashboard in time for 3:30 presentations. So I decided I was going to compare the flights in January 2019 to those in January 2020, before the flights started to decrease due to Covid-19. Once I chose what data I wanted to analyse, I started by downloading the data from January 2020 which took a few minutes as the data is split into separate folders, each containing information about an individual flight. Once downloaded, I had to extract the data. To do this however, I had to download 7zip, as my laptop kept freezing every time I attempted to extract it otherwise. With 7zip, it took approximately 40 minutes to extract.

In the meantime, we had Jonathan Sherman help us create a macro to be able to import all the downloaded files into Alteryx so that we could format them and then load it into Tableau.

The macro was easy enough to understand but when actually using it with the downloaded data, any changes to the flow, would take up to 15 minutes to run. The final flow looked as follows:

I only managed to load my data into Tableau after lunch time as it was a slow flow to run, although filtering and sampling the data made it a lot more workable.

Dashboard

Finally I had to try find some insights to create my dashboard. At this point, I had luckily already created my Mapbox map and loaded it onto Tableau, which did not take very long.

Once in Tableau, I first created the map, as it was the basic requirement. Next up, some BANS, mainly because this is a KPI dashboard and the objective was to give a clear overview of the data. Finally, I had some time to spare (and too much space left on my dashboard), so I decided to create some complimentary graphs to add more insight. The final result was…

You can find my Viz in Tableau Public in this link:

https://public.tableau.com/views/DashboardWeek-Day2/DashboardWeek-Day2?