Key Australian
Government Actions Example Outcomes Underpinning Science Example Applications
Initiatives
• Australian Data Strategy
• Australian Cyber Security Growth Network
• Next Generation Technologies Fund &
Defence Innovation Hub
• Biosecurity Advanced Analytics Capability
Regulations
• Privacy Act 1988
• Treasury Laws Amendment (Consumer Data
Right) 2019
• Improved decision making across all sectors
using pooled data
• More accurate risk assessments
• Improved public and individual health
outcomes from predictive health models
• Improved processes and productivity in any
industry from construction to tourism
• Enhanced recruitment and strategy
development for sporting organisations
and businesses
• Improved lean manufacturing processes to
reduce waste and improve time efficiencies
in monitoring and controlling the supply and
demand of products and services
•Efficient management of equipment for
mine operations
• Improved farm productivity, and adoption
and commercialisation of research
through targeted data that provides early
intervention and actions for producers
ANZ Standard Research Classification Category
• Applied Mathematics
• Mathematical Physics
• Numerical and Computational Mathematics
• Software Engineering
• Data Management and Data Science
• Theory of Computation
• Quantum Physics
• Statistics
Readiness Level – Now
• Business and market intelligence, including
targeted and customised advertising and
recommendations
• Forecasting the spread of infectious diseases
• Risk modelling, credit ratings and fraud
detection for financial institutions
•Bushfire prediction and analysis
• Cyber threat analysis
• Medical research and DNA analysis
Readiness Level – 2–5 years
•Predictive modelling of complex systems
(traffic, energy, weather, climate change,
public health, crime, financial markets,
etc.) for enhanced decision making or
early warning and response
Readiness Level – Beyond 5 years
• Human-machine symbiosis for enhanced
decision making
•Accelerated scientific discovery – extraction
of scientific knowledge directly from
experimental data
Systems, processes and techniques for analysing
large volumes of data (i.e. ‘big data’) and
providing useful and timely insights, usually with
limited human intervention. Applications for
advanced data analytics include medical
diagnosis and treatment, acoustic analytics,
regulatory compliance, insurance, climate
monitoring, infrastructure forecasting and planning,
and national security.
Advanced Data
Analytics
Key Sectors
Influences all sectors of the economy, including:
• Agriculture
• Banking & Finance
• Communications
• Defence & Defence Industry
• Energy & Environment
• Health
• Transport & Logistics
• Education & Research
• Mining & Resources
• Manufacturing
• Space
Opportunities and Risks
Advanced data analytics will have a significant impact on Australia’s economic prosperity and national security. The ability to
efficiently analyse large data sets to identify useful patterns and trends, using machine learning, will underpin faster and more
responsive decision making across society. For example, the ability to analyse datasets for population groups will help identify those at
risk of environmental or heritable health risks. Data analysis will also contribute to farm productivity through better informed cropping,
chemical usage and livestock management; greater use of data will provide more efficient processes and management across all
sectors. In turn, advanced data analytics will result in increased operational efficiency and reduced operating costs across sectors,
increasing our economic prosperity.
Whilst large data sets are invaluable for identifying trends and insights to improve decision making and forecasting, poor decision
making and unwanted outcomes may result from biased or incomplete data, or poor analysis of the data, with impacts ranging from
minor inconvenience to physical harm. Cyber security risks, including data security, privacy and identity theft, need to be addressed
wherever large sets of data are collected and used. National and international initiatives are setting standards and frameworks to
address and mitigate these risks, together with improved public awareness, consumer data-empowerment, and understanding
of data collection, usage, privacy and security. Measures are also necessary to ensure that capabilities to accurately profile and
measure sentiment in individuals and targeted groups are not used to undermine Australia’s social cohesion and democratic values.
In addition to the identified risks associated with data analytics, in order to realise the benefits of our research strengths, we need to
ensure we have adequate data infrastructure to collect, store, manage, access, share and analyse large volumes of data.
Australia’s place in the world
The United States and China are closely matched for research impact in
this area, ranking 1st and 2nd respectively. Four of the top 5 international
research institutes are in China. Advanced data analytics is an area in
which Australia has considerable research strength. We are ranked 5th
internationally for research impact, with the University of Wollongong
ranked 3rd internationally. Australia has 5 institutes in the international
top 50, including the University of Wollongong, University of Melbourne,
University of Technology Sydney, University of New South Wales and the
University of Sydney.
The United States has slightly more venture capital (VC) investment than
India, and both have considerably greater investment than China (3rd).
Australia ranks 16th globally, while worldwide VC investment has been
increasing by around 49% p.a. since 2016. China has the greatest
number of patents in this area, with more than 5 times that of the United
States (ranked 2nd). Australia ranks 14th. Patents for advanced data
analytics have increased by 22% p.a. since 2016.
India is also highly ranked for research impact (4th) and VC investment
(2nd), consistent with their emerging strengths in data technologies.
Estimated impact on
national interest Low Med High
Economic Prosperity X
National Security X
