Dashboard Week


Dashboard week is an infamous week marked on every Data Schooler’s calendar where, for every day, you’re given the task of creating a new dashboard and writing a blog for that day. I missed my cohort’s Dashboard week, and have since been catching up whilst (attempting) to adhere to the strict one-day time block. Here’s my work for the fourth and final Dashboard week challenge, in which everyone had to create a Boston 311 Calls Dashboard. Click here to see my previous challenge.




The final day of dashboard week involved creating a dashboard analysing Boston 311 Calls, taken from the Boston website. The 3-1-1 number provides access to non-emergency services, like animal rescue and fallen trees.


Data Preparation


The data preparation in Alteryx was relatively straightforward. I brought in a table to join to the main table that had each department’s name, so they weren’t simply identified by an abstract code. After some general prep and date/time parsing, I classified each call as either during the day or at night by a formula using a time field. My intention was to see how each department’s calls differed at night across Boston.



With my final dashboard, the whole aesthetic was based on calls made ‘after dark’, and so a dark grey/black colour scheme contrasted with a vibrant neon yellow allowed insights to be visually conveyed.

I wanted to include a spatial aspect to the final dashboard, and a density map made sense in the context of a small geographical area like Boston. To deliver further information on a chart that was fairly abstract, I created another marks layer on the map to show the call breakdown for that particular zip code. Alongside this map, details pertained to the overall night/day ratio and information about the department filtered on. I had yet to try a waffle chart, and thought the night/day ratio provided a great use case, so I gave it a shot!

You can view and interact with my final dashboard on my public Tableau profile here.

Joshua Verbeek
Author: Joshua Verbeek

Josh completed a Bachelor of Psychological Science in 2021, with a focus on research. He discovered a great passion for analytics through the degree. Following graduation, he joined a Market Research graduate program working in data engineering. His decision to join the Data School resulted from a desire to perform analyses, gain insights and communicate results in a visually engaging way. Having previously studied and worked within Graphic Design, Josh is particularly interested in the way data is visualised and presented.