Australia a hotbed for data analytics

Market for technologies that help organisations make sense of vast volumes of data is hotting up Down Under

Faced with rising fuel prices, motorists in Australia have been turning to petrol apps that use big data to find the cheapest pumps across the country.

Take FuelCheck, for example. The smartphone app developed by the New South Wales state government enables people to see immediately which petrol station in their vicinity is selling the cheapest fuel. Other states are expected to follow suit.

In 2016, the New South Wales government’s minister for finance, services and property, Victor Dominello, drove legislation obliging petrol stations to publish fuel prices online as they were changed. This real-time data is now being used by apps such as FuelCheck.

“Rather than playing Russian roulette, I can go from here to Parramatta and know in real time that the petrol from this station is 20 cents cheaper than the one down the road,” says Dominello. “This gives you that visibility – it’s a very simple analytics tool for the consumer that can save you $500 a year on petrol just by being smart.”

For both public and private sectors, data analytics offers this sort of hip pocket outcome across multiple areas.

According to technology research firm Gartner, the global business intelligence and analytics software market will grow by 7.3% this year to reach US$18.3bn. In Australia, this market is expected to surge by 13.4% to A$889m (US$684m).

“Australia has moved from first- and second-generation business intelligence into advanced and visual analytics,” says Julian Quinn, regional vice-president for data visualisation specialist Qlik. Data literacy in the country is fairly good compared to Southeast Asian countries, particularly among Australian companies with a global footprint, he says.

Great opportunity

Quinn also notes the great opportunity for Australian organisations to improve decision-making and competitiveness by using data analytics. Much of this is driven by the widespread availability of data from internet of things (IoT) devices and social media, which can now be harnessed with tools that make use of big data and cloud technologies to support effective decision-making.

“We believe that data and analytics will have the same impact on our society as the internet did over the last two decades, especially with machine learning,” analyst Kurt Schlegel said at this month’s Gartner Data and Analytics Summit.

And just as access to the internet was democratised, Gartner is forecasting a rush towards tools that will put data in the hands of every worker to support them in their jobs. It will no longer be the province of data scientists.

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Indeed, Qlik’s business in Australia has doubled in the past year, with customers such as Qantas, Harris Farms, major banks and healthcare providers using its self-service and visual analytics tools.

Australian startups such as Hyper Anna are also getting into the act. Using machine learning techniques, the company’s data analytics system enables anyone to query a body of data using natural language. It recently secured A$1.25m from Westpac’s venture capital arm, Reinventure, to continue work on its platform, which is hosted on Microsoft’s Azure cloud.

On the fleet management front, Melbourne-based IoT technology company Connexion Media has developed a telematics service that takes data from in-car sensors to deliver insights to fleet managers about where their cars are located, fuel consumption and how the cars are being driven. The system is also the basis for a similar service from General Motors in the US.

Schlegel and fellow Gartner analyst Ted Friedman say such cost-effective and ease of access to data will drive the exponential growth of data and analytics to enable “a massive injection of empirical decision-making and intelligence into our workforce”.

Rethinking data

Large organisations that are managing huge and growing collections of data will need to rethink how they collect data to realise the full benefits of data analytics.

The New South Wales government is already building a data lake to store all manner of information – from petrol prices to green slip car insurance claim forms – which can be trawled for value and insights, and potentially new services. It is also investing A$17m over four years in a data analytics centre, which Dominello says will pay for itself in the short to medium term, thanks to the insights and operational efficiencies it promotes.

But Gartner warns that dealing with huge volumes and varieties of data will require a fresh approach to data management.

Friedman notes that although classic data warehousing, batch processing and relational databases have served organisations well, they start to break down in the face of digital businesses that handle massive data volumes and streams of data from IoT devices.

He predicts a rise in capabilities for in-memory computing, stream-oriented architectures and data virtualisation. In particular, Gartner has forecast that by 2018, organisations that embark on data virtualisation will spend 40% less than their peers that do not have the same capability.

The essential Ds of data

Having championed the New South Wales Data Analytics Centre, Victor Dominello, minister for finance, services and property in the state government, is adamant that data can add value to every organisation. But he stresses that organisations must focus on the essential “Ds of data” to reap maximum value. These include:

  • Digital: If you love paper, do origami. If you want to work in the 21st century, it has to be digital.
  • Direct: If you can get data in real time, you will start seeing seriously deep insights, making decisions in real time and using predictive analytics.
  • Display: We are visual creatures and need to look at things, ideally on a display and on a map so you start to see patterns that lead to insights.
  • Dissection: You need the analytics piece, creating insights to operationalise what you can see to drive better outcomes and efficiencies.
  • DNA: This has to be cultural – using data needs to become the default position.
  • Third dimension: augmented and virtual reality technologies are poised to take data analytics to a new level.

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