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Dashboard Week: Bringing Supplementary Data to Enrich Dashboards!

This post was originally published on The Data School blog between 2018 and July 2025, before our program was renamed to MIP’s Analytics Career Accelerator. References throughout this article to “The Data School” or “DS” all refer to what is now MIP’s Analytics Career Accelerator. The program, its people, and its commitment to launching outstanding analytics careers remain the same – just under a new name.

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Dashboard Week: Day 3

As mentioned in the last posts, the Data School is in the Dashboard week. And, today’s challenge was to create a dashboard using England’s House price index data set. (access the data: https://data.london.gov.uk/dataset/uk-house-price-index)

 

Dataset

While the data was well structured, I needed to clean and prep the data in order to reduce the size so that I can only deal with the data I needed for the dashboard (only London boroughs). 

So, in the end, I reduced it to 4 columns (Boroughs, Date, Code, and the Price). However, since the data was rather small and simple, in that, it only had data and prices for London Boroughs, I brought supplementary data.

 

Supplementary Data

I found that there are areas called Opportunity Areas and the OAs dataset the London government has released. (https://data.london.gov.uk/dataset/opportunity_areas)

Opportunity Areas (OAs) are London’s major source of brownfield land which has a significant capacity for development to accommodate new homes, jobs and infrastructure of all types. They are linked to existing or potential improvements to public transport and typically have the capacity for at least 5,000 new jobs or 2,500 new homes, or a combination of the two.

 

Tableau Dashboard

When bringing a supplementary dataset, there is an opportunity for Tableau builders to enrich their dashboards or even focus their dashboards around the dataset. And, this is what I did with this dashboard.

As you could tell, the first screenshot has two charts that show the house price index from the original dataset. And the charts in the second screenshot differentiate Opportunity Areas and Non-Opportunity Areas. And my whole dashboard was focused on the opportunity areas.

I hope you took some ideas from my approach to direct my challenge by focusing on a small portion and bringing supplementary data to create a focused and interesting dashboard.

 

 

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