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Team Name:

The Nav1gators


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Evidence of Work

Start Here App

Project Info

The Nav1gators thumbnail

Team Name


The Nav1gators


Team Members


4 members with unpublished profiles.

Project Description


Individuals not in employment, education or training who are interested in running their own business may be eligible for New Business Assistance with NEIS. But how will they know if it's a good idea to start their business and how will they know where to open it?

The Start Here app will show users up to date data on business locations and success rates using open government and real estate data.


Data Story


We wanted to design an app that would display information that is relevant to people wanting to start a small business. The app is meant to be used as the first step in researching the area and market before you start. Therefore the information is presented in a simple and clear way so users can quickly get an idea of where to start.

The information shown to them is the amount of a certain business type in a specific area, how this compares with the number of other types of business and the success rate of this type of business based on past small businesses.

The user simply enters their desired business industry and location and the app will use real time data analytics to visualize and assess the quality of their decision.

We used four data sets to achieve our goals:

Past NEIS recipients summary data - when the user enters there desired industry and location the app will compare the selection to similar businesses success rate and show the user a suitability value for their decision.

Business establishments data - Contains information of the number of business in a certain area in each industry. We use this data to visually show the user where certain types of businesses are clustered. The user can then make a decision on where they want to open their business.

CLUE small area data - The region of Melbourne we are focusing on is broken down into 13 small areas and over 600 blocks. This data set contains geometry data for the boundaries of these areas. The app uses this to draw a map that the user can then interact with gather more information related to their business idea.

Melbourne landmark data - Contains descriptions and locations of relevant landmarks in Melbourne. The app uses this to provide added information about each small area that may be relevant to someone opening a small business.


Evidence of Work

Video

Project Image

Team DataSets

CLUE small area and block maps

Description of Use Used to draw the map of Melbourne and split it by block

Data Set

Business_establishments_per_block_by_ANZSIC

Description of Use Used to show the user a color scale based on the number of business in an area selected

Data Set

Melbourne City Landmarks - Historical Images

Description of Use Used to provide a list of nearby landmarks.

Data Set

Data for New Business Assistance with New Enterprise Incentive Scheme (NEIS)

Description of Use Using past NEIS data to predict the success of future business

Data Set

Challenge Entries

Helping Start-ups and New Small Businesses in Australia

Choose one of the following questions to address: 1. What trends in business activity can help encourage self-employment through NEIS? 2. What type of NEIS businesses are being started and are successful (participated in the full 12 months of NEIS Assistance) and what can we learn from broader industry growth areas? 3. How do we encourage self-employment through greater participation in NEIS for cohorts currently underrepresented?

Go to Challenge | 21 teams have entered this challenge.

Efficient Visualisation

Immersive visualisation to understand data

Go to Challenge | 11 teams have entered this challenge.

🌟 Small Business; Big Decisions

Where you choose to open a business plays a big role in whether you succeed or fail in small business. Many business owners make these decisions based on gut-feel or by doing extensive desk-research. How might open data help small business make better decisions?

Go to Challenge | 13 teams have entered this challenge.