Last Friday, I and my fellows DSers presented our first client project since the beginning of our studies. So far, every Friday, we had the opportunity to watch DS12 client project presentations, while we would produce a presentation based on some data provided by our coaches, but not linked to any specific client. Hence, this represented an important milestone for our cohort, from now on this will become our weekly routine.

Our first client was an organisation for children well-being based in Canada.

The project started on Monday when we had our first contact with the client organiser, our point of contact. Given the time difference, we had this call during the afternoon (unlike the usual client projects). During this call, she explained her company background, told us about her use of Tableau and explained in depth the 3 challenges she had for us DSers.

Tuesday was the day in which we actually started to work on the project. Lead by Robert, we started to discuss data preparation and ideas of visualisation for each of the 3 challenges. We then divided into different groups, each of them with the aim to tackle a specific challenge. I personally worked on challenge 2, in a group with Hanna, Debora and Sam.

Our challenge consisted of creating a visualisation that would make easy to spot pockets of income poverty within a neighbourhood area. We also had an additional request, try to embed Canada’s census data within this visualisation.

In contrast with our initial forecast of 3 hours, pretty much all Tuesday and the afternoon session of Wednesday were dedicated entirely on data prep. The part I initially thought would be the trickiest (matching 2 different spatial files) was actually the easiest. We solved that with a simple flow in Alteryx.

For all the remaining data Prep, we were asked to only use Tableau Prep Builder, in order to make our projects replicable from our clients.

And here is where we started struggling. The amount of data we found in the census was huge, and the formatting was far from user-friendly. We really tried hard to include all this information in the visualisation, although on Thursday, we had to face reality and we started to create a draft of our visualisation with the data we had.

By the end of Thursday, we had a functional dashboard that delivered the aim of the challenge. On Friday morning we polished the overall view and we practised the actual presentation.

I’m personally very proud of what we achieved. We created a dynamic map which zooms in the neighbourhood area, showing all different census tract (a sub-area of the neighbourhoods), colour coded by income.

The company organiser was really impressed by the work we managed to produce in this amount of time, and Andy gave us very positive feedback too.