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Team Name:

Data Revolution


Team Members:


Evidence of Work

Datafields

Project Info

Data Revolution thumbnail

Team Name


Data Revolution


Team Members


Lukas M-M , Gabriel Rus , Steve Pratt , Jacob , Muhammad , Husan , Ruggie and 1 other member with an unpublished profile.

Project Description


No one likes being left behind. To stay competitive, Australia must move fast to become Asia-Pacific’s leading AI and cloud hub. The CSIRO estimates digital technologies, including AI, could add $315 billion to our economy by 2028 [1]. The question is: how do we get there?

The answer lies in data centres.

Think of them like airports. Airports connect people to the world; data centres connect us to information, AI, and digital services. If an airport is too far away, travel slows and opportunities are lost. The same is true for data centres: their location shapes speed, reliability, and whether businesses and communities can truly benefit from emerging technologies.

But just like airports need smart planning and clear flight paths, data centres need intelligent placement and public trust. And with billion-dollar investments already coming from Amazon, NextDC and Goodman Group, the time to act is now.

Introducing Datafields — the latest solution from Team Data Revolution.

Datafields is an advanced analytics platform that helps policymakers, energy providers, investors, and communities plan the future layout of Australia’s data centres — and the energy they’ll require.

It has two key components: data-driven location intelligence and an interactive simulation.

With location intelligence, Datafields analyses infrastructure, energy, and geography. Using the Digital Atlas of Australia, we mapped power stations, transmission lines, and fuel types — essential for assessing if a site can sustain a tier 1 through to a tier 4 data centre, which often need multiple, diverse power sources and redundancies.

The simulation lets users set a budget, pick a site, and design a data centre profile. It shows construction costs, IT capacity, uptime guarantees, latency to nearby communities, and the grid impact. We integrated Australian Bureau of Statistics (ABS) population and Consumer Price Index (CPI) statistics to project demand growth and energy needs, ensuring decisions aren’t just good for today but also sustainable long term.

And here’s where AI makes a difference: Datafields doesn’t just throw numbers at you. It interprets results in plain language. Instead of “x megawatts required,” it tells you:

-Is this site affordable?
-Is it sustainable?
-Will it stress the grid or benefit the community?

This transforms raw data into actionable insight, building trust and clarity for decision-makers.

The purpose of Datafields is simple: smarter, more transparent decisions about where to build and how to power Australia’s digital future.

This isn’t just about servers. With Datafields, Australia can cut through the noise, plan smarter, and secure its place as the digital powerhouse of the Asia-Pacific.

Let’s build it wisely.

Join the mission. Try Datafields today.

[1] https://www.industry.gov.au/publications/list-critical-technologies-national-interest/ai-technologies


Data Story


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Team DataSets

Data and Digital Government Strategy - Implementation Plan - December 2024

Description of Use We used this data set to evaluate the importance of data centres for Australia's data and digital future.

Data Set

Consumer Price Index, Australia

Description of Use We used this dataset to calculate the average annual consumer price index (CPI) percentage increase, considering the period 2016 - 2025.

Data Set

Population clock and pyramid

Description of Use We used this data set to calculate the average yearly population increase for Australia, to include in our simulation.

Data Set

Telecom Australia - Telecom Information Kit No. 4

Description of Use We used this dataset to extract a visual representation of Australia's telecommunications lines to analyse further.

Data Set

National Electricity Market Data Dashboard

Description of Use We used this dataset to extract electricity prices for use in calculating the cost of electricity for data centres.

Data Set

Data Center Tiers Explained

Description of Use We used this dataset to extract values on uptime guarantee and component redundancy for the 4 tiers of data centres.

Data Set

Data centres: When to include them in electricity demand forecasts

Description of Use We used this dataset to determine the cost of construction for a data centre. This dataset stated that as a general rule it costs between $9 million to $14 million per megawatt (MW) of commissioned IT load to build a complete data centre.

Data Set

Equipment Guide for Data Centres

Description of Use We used this data set to familiarise ourselves on the different considerations for a data centre.

Data Set

Electricity Transmission Lines

Description of Use We used this data to determine the breakdown of class and location for operational electricity transmission lines in Australia. Additionally, we calculated the total and average length and capacity of these electricity transmission lines.

Data Set

Power-hungry data centres scrambling to find enough electricity to meet demand

Description of Use We used this data to extract the estimative total electricity demand of data centres in Australia in 2024 and 2030, based on scenario A (8% usage of the electricity grid in 2030) and scenario B (15% usage of the electricity grid in 2030). For both scenarios, we determined the average yearly growth in electricity demand and the electricity demand in MegaWatts (MW).

Data Set

Major Power Stations

Description of Use We used this data to determine the breakdown of class (renewable vs. non renewable), generation type, primary fuel type and location for operational major power stations in Australia. Additionally, we calculated the total and average electricity output of these power stations.

Data Set

Challenge Entries

Data Centres: A Cornerstone of Australia's AI Future

How can we analyse Australia's infrastructure, energy, and geographic data to select locations and operational strategies that will position Australia as the Asia-Pacific's leading AI and cloud computing hub?

#Data-centres-for-2050

Eligibility: Open to all. Teams should use at least one government dataset in their solution, with preference for creative combinations across different data types (infrastructure, energy, telecommunications, geographic, climate, economic, or planning data). Proposals should include clear methodologies for data integration, analysis algorithms, and implementation planning with consideration of real-world deployment challenges

Go to Challenge | 13 teams have entered this challenge.