A reflective redesign of my initial tableau application to The Data School for DS37.
The Brief
Over the past two weeks we have explored best practice in data visualisation and utilising often overlooked abilities within Tableau (such as dynamic measures). Today we were challenged to reproach and redesign one of our initial applications to The Data School; whether that was out first application or our final application.
I decided to take an approach towards redesigning my first application - an overview and analysis of Video Game sales across 4 core regions (North America, Europe, Japan, and a broader 'Other' region). This visualisation primarily looked at a breakdown of video game sales per region, before exploring the difference is publisher and platform preferences. I received feedback regarding the length, detail, and lack of white space within this initial application. The scope I began with lacked direction, and attempted to ask (and answer) too many questions, utilising the entire dataset to the detriment of overwhelming the user with information. However, positively, good feedback was received on my chart interactions, region parameters, colouring decisions, and genre interactivity iconograph.
The Redesign
Utilising this feedback, and the experience gained over the past two weeks, I decided to redesign my visualisation into my first attempt at making a user-focussed interactive dashboard. Below you can see a rough redesign sketch, generated using Excalidraw:
This redesign provides a brief overview on what I thought a condensed version of my initial visualisation could look like. This redesign would utilise a similar colour scheme, and retain the region selection parameter (found at the top left). It would also retain the genre control options at the base of the chart area in the centre of the design. This charting area would also utilise a dynamic chart parameter, to flip between a historic genre performance and information on the individual games, charts retained from the first iteration. The first of the two would also utilise a grouped histogram to provide condensed information regarding the change in performance of genres over 4 decades (1980-2020). The redesign also provides 3 bold information boxes at the top of the charting area, these boxes can be used to provide quick information regarding sales, platform, and genre performance per region.
This redesign would simply answer the question of genre performance and preference across the 4 core regions, a further future redesign could look at adding further pages into this dashboard to explore publisher and platform preferences too.
The Final Project
With this redesign in hand, I set about recreating my initial visualisation from a brand new mindset, resulting in the following (found here):
As observed above, the redesign was strongly followed, with the region and chart type parameters utilised in a band across the left of the dashboard, separating, and giving space to the wider information. Following on from the feedback received, the graphs, charts, and text within the dashboard were given more room to breath, and the colours were restricted to neutral tones as to make interaction easier on the end user.
As seen in the image below, the highlighting and filtering using the iconogram was retained from the initial dashboard, utilising and encouraging interaction by the end user to explore the data. Furthermore, upon selecting a genre, a 4-decade histogram appears showing the distribution and change of popularity in the selected genre across the time period. Towards the right of the image, there is a relative performance tracker per genre, identifying how customer behaviour preferences change per genre - presenting purchases per titles released per genre.
In changing the chart parameter towards the left-hand side of the graph area, we can view a chart (as seen below) that explores the individual titles, and their performance within the region. The relative preferences chart is unchanged, but the genre selection tool still performs as required. Within this second chart, the user is able to explore the individual titles, seeing a breakdown of information within the tool tip. This utilises a hidden, or hard to find, graph that was generated for the initial visualisation.
A Reflection
As previously mentioned, this new dashboard utilises a small amount of data from the original data set, and could be improved upon by adding a page selection, to further explore information on publisher and platform preferences.
However, as an initial idea formation, this dashboard explores differences in regional preferences and provides opportunity for end user exploration of data. This was a good opportunity, to implement refined dynamic parameters and sets to aid in exploration. Furthermore, newly implemented colour theory has made the dashboard easier on the eyes for an end user.