Business empires in Australia

"Build your children's future!" is a calling that has drawn immigrants to Australia for the past 250 years, following European colonisation of Aboriginal land. People have packed their belongings and headed to the land of (uneven) opportunity, put down roots, and started businesses. Digging through Australia's business name register, so much information is revealed about the country's industrial development and how it has shaped modern-day Australia.

data visualisation interactive maps

Author

Jack Zhao

Date

February 2020

Key points:

- "Michael" is one of the most common names found in the ABN register.
- "Consulting" businesses dominates the North Shore and Eastern Suburbs in Sydney, while "transport" businesses claim large areas in Western Sydney.
- Non-Anglo names, such as "Nguyen" and "Singh" are often associated with transport, international trading, and property businesses.

The maps

The data behind these maps come from ABN (Australian Business Number) data, the ABN Bulk Extract. This data contains publicly available information supplied by businesses when they register for an ABN.

Using Natural Language Processing (NLP) we identified names of people and industry sectors within the business names in the ABN dataset. For the businesses in each postcode area, we identified the most frequent names and industry sectors, and mapped their geographical range. Areas that share a most frequent word were merged. The result manifested as collections of small 'empires' whose borders are defined by industry sector and ownership profile.

The maps aim to demonstrate the history of immigration, through the lens of both the business owner's country of origin (inferred by name) and their main business activity. These maps are useful for showing large scale patterns - large swathes of land forming empires of 'transport' for example, or owned by people with the surname 'Kim' (Probably different people, but likely to share cultural background). For individual locations, the maps only show the most common word, the diversity of the full set of identified words is omitted by design. The caveat is that there may be very little difference in count between the first and second highest ranking words for an area.