Get your data ready for
Machine Learning that
delivers business results
Data-related challenges are the biggest blocker to adopting ML
That’s according to our Machine Learning in Australia National Pulse Report 2021. We surveyed over 200 organisations to find out why this transformative technology is not yet being adopted at the rate it should be.
It may come as no surprise to hear that the majority of our respondents had data-related challenges, ranging from regulatory and privacy concerns to a lack of infrastructure and strategy.
Download our report to not only unearth insights and tips on how overcome data challenges, but also find out what’s preventing more organisations converting an interest in ML into success.
Download the DiUS ML report
DiUS Machine Learning Leads Nigel Hooke and Nabi Rezvani outline how to measure data quality and readiness for ML. They also outline some common data readiness challenges and how to build the necessary data infrastructure.
When DiUS partnered with Solve Geosolutions on a project, the two companies successfully reinvented the process for geologists to analyse drill core samples to generate geological information but also discovered a new area of opportunity for a new machine-learning powered software product to improve the mineral discovery process.