For the third day of dashboard week, we’re given a dataset on the UK house price index from this link. It has data on the average price, price index and volume of sales of houses in the UK broken down by London boroughs and regions. We’re also provided with spatial files if we want to create maps on Tableau.
From these resources, we need to:
- Find additional data to supplement
- Create a Tableau dashboard
- Write a blog post about our work
I first went to the open data from the UK government to see what information they have that I can use to enrich the house pricing data. And what sparks my curiosity was whether the high house prices in London have some relationship with homelessness. So for this day, I spent more of my time researching the topic and searching for datasets, and I just thought it was interesting to go against my suggestions the previous days to try creating a larger dashboard.
There are some limitations when approaching the topic ‘Homelessness’. The official government statistics measure the Statutory Homelessness – people who reported being homeless without taking into account those who don’t. There are numbers on ‘Rough Sleeping’ which measure that but are mostly based on observation and not recommended to be used to see on a year trend basis.
In the end, as I thought before, coming up with a long scrolling dashboard emphasising stories within one day is hard especially if you do additional research on topics you don’t know yet and search your own datasets. But it’s a good experience nevertheless.
Don’t be afraid to try what you think will be too hard to pull off in just one day. Even if you fail and don’t come with a dashboard that you like, it’s still a good learning experience and you discovered how far you can go. But if you want to build a dashboard which ‘wow’ your audience, focusing on fewer things but polishing it to be really good, will perhaps work better.
If you have any questions, feel free to ask me on Twitter or Linkedin.