Helping small businesses make better decisions

Supported By: 
City Of Melbourne

Best Hack that helps small business


Eligibility Criteria

Use at least one city of Melbourne dataset


Team Name: 

Project Description

Data analysis and data journalism project, focussed on the causal factors of Family Violence within Victoria.

These informed data findings, discussed in a high level overview, data journalism format, will allow stake holders to gain an in depth understanding of key factors that drive the reduction of family violence incidents.

This data analytics and predictive modeling research will be utilized to visually depict relevant factors, trends and recommendations in family violence issues.  

Skip Work

Team Name: 
Skip Work

The world around us is rapidly changing - driverless cars, AI, molecular gastronomy, robots and augmented reality.  What does future employment look like for the prep students of 2016?  This hack uses data from ABS, Department of Education and Training mashed with vox pop interviews to project into the future to see which regions of Australia will experience a rapid shift in its employment base: mining towns, manufacturing heartlands and clerical suburbs.  


Team Name: 
Team Zr0


IP Australia has released their data on administered patents and trademarks. We generated a series of visualizations based on these statistics. Applications were grouped by status, application type and location, both state-level and country-level. 

Difficulties faced

  • Large dataset
  • Instructions unclear

Tech Used

  • Power BI
  • Microsoft Azure storage


Team Name: 
Four Planners and a Panda

SweetSpot is a data visualisation tool which combines employment, building, residential and traffic data in Melbourne to determine promising locations to start or expand a business.

It allows users to interrogate a wide range of property, landuse and demographic datasets at an individual building level, with the aim of helping users suitably locate a business.  The tool allows for the interrogation of: