“Machine learning” and “deep learning” are often considered interchangeable terms. Both are statistical modelling techniques, both can be used for making predictions, one is a subset of the other and they are both subsets of artificial intelligence.

Big data can be an important tool for business. When it’s properly harnessed, it can provide insights that can lead to smarter growth and stability strategies. However, big data is only effective if it is effectively interpreted. As the individuals who make business decisions are often not the same people who extract data, it’s crucial that the data’s meaning is presented clearly. This is why data visualisation is a critical element of data analysis.

Over the past several years, data scientists working in the corporate world have transitioned from being ancillary providers of value to becoming key players in shaping their firms’ corporate strategies. This evolution has occurred as part of a larger trend of digital transformation. This transformation includes efforts by businesses to centralise their data and integrate analytics-driven insights into both their traditional and non-traditional product and service offerings.

Despite efforts in recent years to significantly increase the number of cyber security professionals in Australia, there still remains a significant shortage, according to the Australian Computer Society.

In a world driven by data and digital infrastructure, safeguarding information systems is a critical priority for individuals, organisations and governments alike.

The tech revolution has transformed how we live, work and connect, but it has also introduced serious vulnerabilities and security threats.

Cybercrime and security breaches already cost the Australian economy an estimated $30 billion dollars annually and as digital transformation accelerates, so does the complexity and scale of cyber threats.