Today marks the beginning of Dashboard Week, and when I first saw the data, I was overwhelmed and unsure of how to proceed. Terms like “Dragons” and “Starlink” left me feeling confused and lost. However, after conducting research and consulting with ChatGPT, I gained a better understanding of the data. I found myself drawn to the launch and launchpad data, as I believed it could be used to tell a compelling story about SpaceX’s missions. At that time in my mind, I already decided to have some metrics such as the number of launches, success rates, payload types, and launchpad locations.

Data Preparation

The data preparation process took longer than expected though I only used two datasets, but in order to join them and avoid duplication, I have to make sure the launch pad and launches are in the same granularity level.


In tableau, I incorporated a new measure after asking chatgpt, I used the time difference between the launch time and static fire time to estimate how much time was spent on testing and preparation which is called turnaround time. Static fire test is a critical step in the process of preparing a rocket for launch, as it verifies that the rocket’s engines are functioning properly and is typically done a few days before the scheduled launch date.

Finally, after hours of hard work, I finally completed my dashboard. It was a challenging but rewarding day.

The Data School
Author: The Data School