It’s now halfway through Dashboard Week and so far I have been really enjoying it! Each day I get the opportunity to creatively solve problems and come up with unique methods to achieve a certain technical outcome. It is really fun not having any restrictions in that regard, that way I can go ahead analysing and solving problems using the tools and concepts I’ve learnt in a creative way.
Today’s task was to connect to historical data about NSW libraries and create a Tableau Dashboard to demonstrate any interesting analysis or insights. The historical data goes back to 2011, and has a multitude of tables detailing demographic of members, number of item usages, number of libraries, expenditure, and so on.
Selecting and Cleaning the Data
My first step was to find a story within the data, and select a maximum of 3 tables to help support my potential story. I decided I wanted to investigate if libraries are actually becoming a thing of the past, or if they are still demand for libraries by customers and members. The cleaning in Alteryx did take a bit longer than expected as there were multiple ways to structure the data depending on how I wanted to create my visualisations. I spent a lot of time going through the options to find which one would be most efficient and appropriate for the charts I wanted to create.
So far I have really enjoyed the data preparation in Alteryx this week. I’ve been able to successfully build multiple iterative, batch and standard macros to help streamline my process, as well as creatively use the tools to achieve desired outcomes (as opposed to following the standard steps to achieve a more common outcome).
The 3 tables I decided to use were the circulation of items table, the library stock table, and the memberships table. Due to time limitations and discrepancies in the data, I narrowed down the date range to 2017-2022 to minimise time delay.
Building the Dashboard
Like my other Tableau dashboards, I decided to use Figma to create a background for my dashboard. I have really enjoyed the design aspect of the dashboard building, as I can really let my creativity run wild in order to achieve a visually pleasing and aesthetic dashboard. Due to the time limitations of the project, I have opted for a simpler layout, but focused on including numerous story points and text to further support my analysis and story in the data. When short on time, I always recommend prioritising telling a strong story using ‘simpler’ charts, rather than trying to build super complex charts that might convolute the story.
Final Thoughts
Now we have passed halfway on Dashboard Week, I can feel the tiredness start to kick in! Moving forward to finish off the week, I am going to focus on delivering a strong clear story in my dashboards, and only collect a manageable amount of data (rather than going deep down the rabbit hole like I sometimes tend to!).