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Team Name:

The Real Slim Shady


Team Members:


Evidence of Work

Fail-a-corn

Project Info

The Real Slim Shady thumbnail

Team Name


The Real Slim Shady


Team Members


Daniel

Project Description


Governments are good a regulating business but bad when it comes to providing guidance. It is on everyone's radar to grow the economy in areas of high demand or future need, but there is no real way of individuals knowing what will work where, so of all companies that start up, half fail within the first year. If the hard questions about why instead of just the regulatory questions about what were asked up front, new companies would begin their journey in much better shape.


Data Story


Using government grant and investment data to show which industries new businesses are best to start up in was in a 2016 project 'Unveil the Scene'. The same year the project 'Future Proof' used open data to give job seekers a greater perspective on where jobs are likely to be located before they are posted on job sites.
This year our team is going to build on these previous works to develop a single pane of glass interface to guide those with a great idea, and turn it in to a viable business.


Evidence of Work

Video

Homepage

Project Image

Team DataSets

Employment by Industry

Description of Use Labour force availability

Data Set

Median Rent by SA4

Description of Use Display cost of property by SA4 using rental price as the statistic

Data Set

Startup Ecosystem Mapping Report (2014)

Description of Use This report is loaded with tables and statistics on startup and innovation in Queensland. Some data sources are end-noted however a number are not, or exist in paper format not available during the event, so the data stated in the report is used as-is.

Data Set

Australian Innovation Ecosystem (Map)

Description of Use Display support 'nodes' for business startups

Data Set

ABS Regional Statistics

Description of Use Pre-sorted ABS mashup of locality and descriptive statistical/representative data to overlay in regionality selections

Data Set

Queensland Accounts

Description of Use Identify industries and localities where spending is directed on a Statewide basis, over time. Growth can be identified over a 20+ year history with trends.

Data Set

Funding Recipients

Description of Use Used to identify the postcodes where innovation funding is being allocated, and identify gaps in Regional Queensland

Data Set

Employment Projections

Description of Use Extract growth data and classify industry as a primary, secondary or tertiary industry as each tier breeds more of the next. Over time growth in primary industries leads to growth in secondary and then tertiary as the economy grows up around them

Data Set

Challenge Entries

Tourism Jobs Challenge

How might we determine the future tourism job needs for Queensland?

Go to Challenge | 7 teams have entered this challenge.

Most Commercially Viable Project

Most Commercially Viable Project

Go to Challenge | 12 teams have entered this challenge.

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.

Sunshine Coast Commercialisation

How to make business boom on the Sunshine Coast?

Go to Challenge | 11 teams have entered this challenge.

Out of the Box - New take on data for regional development

Use an existing data set outside its normal context to both display and encourage innovate solutions to regional problems and promote and foster regional economic development.

Go to Challenge | 11 teams have entered this challenge.

Work Life Made Easy

How can we make work life easier for employers and their workforces – now, and into the future?

Go to Challenge | 27 teams have entered this challenge.

On your mark, get set, start-up!

How do startups have the potential increase job demand in the long term?

Go to Challenge | 8 teams have entered this challenge.

A New Start

How can we improve the process of starting or growing a business?

Go to Challenge | 21 teams have entered this challenge.