The Second day of the Dashboard week.

Today we have very clean data on US international travel, which was for the DSAU20 interview for the data school.


Time Boxing

I thought it was an easy task because we don’t need to clean the data. But for a task like this, an interesting story is important. So, I spent hours digging in the data, trying to look for something interesting.

The Good news is I found the story, but the cons are I don’t have enough time to create a dashboard that can make me feel satisfied. And I waste too much time thinking about the insight. I learnt that time boxing is super important, if I can not finish something I planned initially, the timebox can help me to do the right thing by choosing different opinions.



Here is my story. The charted Airlines were impacted by the 2 major events in the first decade of 21st in America, which were 911 in 2001 and the financial crisis in 2008.

  • The Line Chart of chartered departure shows 2 valley points in the US reflecting the 2 major events. The number of Charted passengers dropped down obviously after these 2 events. But the freight is continually increasing. As the data for 2022 is not enough, till the year 2021, it reaches the peak point.
  • In the scatter plot, Miami dominated the passenger freight and the number of departures, before 911, the largest city for charted passengers was Orlando. After this event, it turns to Sanford. All these cities are in the state of FL.
  • After 2008 financial changed. A much lower number of passengers with the controversy of an increasing number of freights. And Miami is no longer the largest city of freight and is replaced by Anchorage.
  • The bar Chart shows the top 20 charted companies of all time with 3 categories of departure, passengers, and freight. Most of them only focus on one area. Either passengers or freight.

Also, there are huge of action in these charts. They can show many insights into different airline companies for different years, cities, and vice versa. Here it is.


In conclusion, I think the second day for me is very good practice for digging into a large dataset. And find some specific insights and stories apart from the general analysis. Also, I think in the next few days and even in the future. I need to draw the time boxing before I do something new and uncertain, even though it seems how simple it is.

Chuck Wang
Author: Chuck Wang