Introduction

For the first dashboard week challenge, we were tasked with extracting data from a Ticketmaster events API and creating a dashboard from it.

Data/Story Preparation

The main challenge of this dashboard was selecting a suitable story from such a vast dataset. Due to the limitations of requests, we had to be careful with our queries and so I had to call small amounts of data with different queries.

The picture above shows the extent of my data exploration. Each container above represents a different call to the API such as:

  1. Sporting events in Australia
  2. NRL events
  3. EDM music events
  4. Music events in NSW

It was a careful balancing act with the queries as we had to ensure that:

  1. It didn’t exceed the amount of API calls
  2. It didn’t take too long to run in the workflow
  3. The data can support our story

In the end, I chose a story relating to ticket prices for sports in Australia and supplemented it with outside data which looked at popularity and their last season’s rank. The workflow is presented below:

Tableau Dashboard

I created a simple 2 x 2 dashboard with simple actions which tried to link the 4 major sports. The left bar chart and scatterplot were from the API whereas the 2 right charts were from census and standing tables of the various sports. From the data, we can see that the team ranks did not have much influence on the price tickets and it was mainly due to venue/location.

Furthermore, I learned that Ticketmaster doesn’t control all the sports event tickets. Ticketek is another company that provides a similar service. To further understand this, we’d need data from both sources as well as a larger historical sample set to compare events/ranks from previous seasons.

My dashboard is presented below:

Nam Nguyen
Author: Nam Nguyen