Our third challenge this week is using London Fire Brigade Incident Records data and additional data related to London to create a Tableau viz. The data set given contains all callouts for fire brigade in London from January 2019 to January 2022. The data is quite clean and straightforward. And with metadata available on the website, we can easily understand the meaning of each fields.

 

Alteryx Workflow

As the data is already really clean, my workflow in Alteryx is quite simple. First I did DateTime parse to get the date fields in correct format. Then Select tool was used to keep relevant fields only and change the data type of some fields. Data Cleansing tool was used to modify some upper case to title case.

 

The new thing I’ve learnt today is using Alteryx spatial tool (Create Points) to make sense of Easting and Northing in the data. The data does contain longitude and latitude, but they are missing in some rows. Therefore in order to get all points of each row on map, I followed the tutorial written by Rob Suddaby from The Data School UK. Also thanks Ricky for sharing this blog to us!

 

Finally I output the data into a hyper file for use in Tableau. The screenshot of my Alteryx workflow is shown below.

 

Tableau Dashboard

In addition to the data given, I also used London Borough spatial file to identify the border of each Borough. After investigating the data in Tableau, I decided to focus on false alarms. I was a bit surprised that false alarms accounted for more than half of all incident records. And this may imply that some waste of resources, including cost and time.

 

Below is a screenshot of part of my dashboard. The complete dashboard could be viewed on my Tableau Public.

 

Ming-Hsuan Lee
Author: Ming-Hsuan Lee