​Big data analysis will target ‘slumlords’: Dominello

​Big data analysis will target ‘slumlords’: Dominello

Plan to improve conditions for vulnerable students in Sydney and across the state

NSW minister for innovation, Victor Dominello, at CeBIT in Sydney

NSW minister for innovation, Victor Dominello, at CeBIT in Sydney

Big data analysis is set to help the NSW government better identify and deal with ‘slumlords’ across Sydney who are cramming large numbers of students into small apartments.

During an address on Monday morning at the CeBIT conference in Sydney, NSW minister for innovation and better regulation, Victor Dominello, said this was one of six projects being worked on by the government’s data analytics centre (DAC).

Certain dodgy landlords were found to have been placing 14 vulnerable students into two bedroom flats, charging up to $150 per person, per week. In August 2014, the NSW government threatened to cut off electricity to these apartments to shut down their practices.

“How do we find out where these slumlords exist? Normally you would probably go out there and knock on a million doors,” he said.

But data could be sourced from DA applications and various energy suppliers to work out that a high amount of electricity and water is being consumed for a particular two-bedroom apartment that would normally have two tenants, he said.

“You could get data from Fair Trading to find out where the complaints are etc. Then instead of knocking on a million doors, you might only knock on 100 with a 98 per cent success rate,” Dominello said.

“That way, we can not only improve the lives of the people in NSW, but improve the access to those that are vulnerable [and provide] better services across our state.”

The DAC is also crunching data generated by Emergency NSW in an attempt to better respond to emergencies and quickly identify the high number of false alarms across the state.

There are 48,000 alarms issued each year in NSW, 97 per cent of which are false.

“If we could use big data to try and break down which of those are real and which are false, and more importantly - use it to say, ‘this is high risk and this is low risk’.

“So instead of sending two [emergency vehicles] to everyone, you might send one truck or a drone in the future. You’ll use big data to use your resources more efficiently, and that’s what we are doing,” he said.

“We are crunching the big data as we speak, whether it’s local government apps showing construction, which results in dust, which results in false alarms … or looking at the energy grid because if there’s a spike in electricity, that produces false alarms.”

Dominello claimed that there isn’t another data analytics centre worldwide with the legislative power that the DAC has in NSW. This puts NSW at the forefront of big data in the world, he claimed.

“We passed legislation late last year that gives us the power to demand data from each of the 160 agencies in NSW government, energy suppliers, and 152 local councils,” he said.

The DAC can demand this information based on the social priorities as determined by the state government and the premier.

“For example, we have an absolute issue when it comes to childhood obesity. It costs us $23 billion just in health costs alone. Imagine if it was just the health [department] tackling this problem – it’s going to be very hard yards to try and resolve that.

“But if we got data from health, if we got data from schools, sports [clubs], and local councils around the facilities they are providing, then we can have a big picture view of this really difficult problem. We can use the resources of the state in a far more efficient way to tackle a really complex problem.

“But I have to stress that all of this data will be subject to existing privacy and confidentiality concerns,” he said.

Dominello claimed that the NSW government will unlock solutions that can be replicated around the world.

“When it comes to big data and analytics, we are starting to start this engine up and it will become a very powerful engine in years to come,” he said.

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