Data science is incorporated into almost every industry in 2019, including the Australian federal and state governments. Big data management generates better information and practices across a wide array of areas and is part of both governments’ plans to improve safety, helping Australia grow as a nation.
Understanding this transformation offers insight into how other agencies can follow suit and the benefits of doing so.
What is big data?
Big data refers to the vast collections of information, which can capture both structured (e.g. names in hospital records), and unstructured data (e.g. CCTV footage, data from sensors and images). Due to the large amount of data this can encapsulate, computer-driven analytics decipher correlations and common threads within this data much faster than any human could.
By analysing trends and running millions of simulations, various agencies and departments can then discover and use patterns that can help make informed future decisions.
In an effort to have more efficient practices and save taxpayer dollars, Australian government agencies are acquiring and using big data at both a federal and state level. For example, predictive analytics is being used to detect tax fraud, and emergency services, such as Ambulance Victoria, are improving resource allocation with the same data-driven technology. Data warehouses (large collections of data from multiple sources) are being modernised, with data being stored, combined and analysed to maximise value.
State and local governments in particular want to make their data visible, accessible and useful to its constituents. This not only makes it transparent and offers the public peace of mind, it also allows external experts to contribute on how to best utilise these vast amounts of information.
This process has already started across different levels of government. Here are five ways different departments and agencies are using data science and big data.
Learn more about how big data can help your agency with a Masters of Data Science from the University of New South Wales, a flexible, online, two-year course that will empower you with the skills and experience needed to pursue a career in data analysis.
1. Internal efficiency
Improving internal efficiency, helping to decrease the time spent on simple tasks, is a key reason behind implementing big data science.
Analytics can greatly influence many aspects of a business and streamline often tedious administrative tasks. This can eliminate hours of paperwork and create time for more important projects for members of respective governmental areas, such as the Australian Tax Office and Centrelink.
2. Environmental protection
Both the CSIRO and Geoscience Australia have undertaken vast data management and analytical procedures for the country’s environmental sustainability and protection. Analytical simulations allow for a more clear understanding of environmental resources thereby informing relevant parties on how to best allocate and deliver water.
Similarly, the Clean Energy Regulator (CER) also benefits from data analysis. The CER administers schemes for measuring, managing, reducing and offsetting Australia’s greenhouse gases. With data simulation, it can:
- Better inform government policy
- Meet international treaty obligations
- Support statistical services.
3. Health and safety
The Australian Institute of Health and Welfare (AIHW) is another part of the federal government that uses big data management and analytics. Collecting and reporting information on a wide range of health and welfare topics, the AIHW uses data analysis to:
- Compile data on the health and welfare of Indigenous Australians every two to three years in the Aboriginal and Torres Strait Islander Health Performance Framework reports
- Analyse estimates of expenditure on health and welfare to inform future budgets
- Conduct reports on the 40 indicators in the National Health Performance Framework in its Australia’s health report
Data has also better managed the demands of processing services in health and aged care through automation and better divided resources after data analysis.
4. Fighting crime
The federal government’s introduction of the National Criminal Intelligence System (NCIS) has been a key tool in fighting crime in Australia, one that is heavily reliant on analysing mass data.
They ran a pilot program from June 2015-2017 and 11,000 searches were conducted across 600 million available records. These searches and simulations were able to provide:
- More informed risk assessment
- An increased ease of discovering information and intelligence
- Greater collaboration across agencies
- Better awareness of existing criminal intelligence and criminality
- New lines of inquiry for investigation
Through the power of big data management and interpretation, the NCIS is expected to continue to provide advantages to assist Australia’s fight against crime.
5. Fraud detection
Fraud detection is a key area where the government utilises data management and analytics to the country’s benefit. Along with other government agencies, the CER responds to non-compliance and fraud, and the Australian Electoral Commission (AEC) uses data simulations to investigate electoral fraud.
Due to the sheer volume of data analysed and observed, simulations are able to find anomalies easier than before. This process is sped along by the highly skilled data scientists and analysts that work across different government sectors. They filter through the extensive data and synthesise the results of the simulation to detect fraudulent behaviour in a very efficient manner.
If the Australian federal and state governments’ innovative ways of utilising data interests you or your agency, the University of New South Wales offers a Master of Data Science course that can give your further insight into the future of big data.
With industry-leading staff, you will gain a great breadth of knowledge for your career in data science and be prepared for a wide range of diverse employment opportunities. Discover what the Master of Data Science has to offer, and see how you can create a dynamic career in data.