Bounty: Unmasking the State / Territory employment data.
How can we unmask the hidden data behind the labour market in our states and territories?
Go to Challenge | 8 teams have entered this challenge.
DataCake
We want to help Australian to be in a better financial situation. Our goal is to avoid another GFC or any other financial crisis. This is the reason why we wanted to work on the challenge related to insolvencies.
Our approach for this hackathon was to integrate large volume of data across multiple governmental agencies and analyse the main contributing factors impacting insolvencies in Australia.
https://public.tableau.com/profile/william6478#!/vizhome/GOVHACK/Main?publish=yes
What we did:
- We integrated more than 20 different datasets from different governmental agencies
- We built a dataset with 200 different variables
- We used a combination of Machine Learning and Advanced Analytics to derive additional information
- We focused on interpreting our models outputs in order to derive meaningful insights. We are against black-box solution
- We built an interactive dashboard to explore all these informations
Our solution helps to:
- Explore different datasets we integrated
- Compare different SA3 areas on the different accessible variables
- Understand the factors that are impacting insolvencies ratio
Go to Challenge | 8 teams have entered this challenge.
Go to Challenge | 13 teams have entered this challenge.
Go to Challenge | 11 teams have entered this challenge.
Go to Challenge | 28 teams have entered this challenge.
Go to Challenge | 28 teams have entered this challenge.
Go to Challenge | 61 teams have entered this challenge.
Go to Challenge | 13 teams have entered this challenge.
Go to Challenge | 19 teams have entered this challenge.
Go to Challenge | 14 teams have entered this challenge.