Blog | AI 

Data and the future: we’re standing at an inflection point

The case has long been made for the value of data and that’s why we’ve seen the emergence and then maturation of business intelligence and related analytics software solutions. But I believe we’re standing at an inflection point where more organisations than ever are going to take advantage of their data to do business in entirely new ways as a result.


Here at Qrious, we’re so confident of this fact that earlier this year we made a major acquisition, bringing on board the personnel and intellectual heft of NOW Consulting. By bringing together the analytics and AI capabilities of Qrious with NOW’s expertise in data integration, engineering and visualisation, we’re focused on helping New Zealand organisations lay the data foundations for an AI future.

And the truth is we’re already engaging with AI in our everyday lives. From voice assistants to automated alerts, chatbots to product recommendations, it’s here. Now it’s time for New Zealand organisations to start putting this technology to work.

A strategic turning point

Data, finally, is shaking off the shackles of local hard drives or even local data centres. It now lives in the cloud where something can be done with it. Most folks will instinctively recognise the latent value of data, but when it's tucked away here, there and everywhere, it has remained just that: latent.

I believe what the cloud brings right now is the opportunity to significantly modernise data architecture to take full advantage of an AI-based future. We’re hitting a game-changing moment, where, as more and more organisations shift their data management practices into the cloud, AI moves from theory to a practical and essential reality.

But why do we want an AI future? Firstly, as noted in the New Zealand AI Forum’s recent report, Towards our Intelligent Future, there is no shortage of major challenges to which AI technologies can be applied – and even relatively small investments in data and AI solutions could lead to substantial gains.

Secondly, to be competitive in an increasingly disrupted digital landscape, New Zealand organisations need to develop a strong digital strategy – and AI should be part of this. In January 2018, McKinsey argued that “If companies wait two to three years to establish an AI strategy and place their bets, we believe they are not likely to regain momentum in this rapidly evolving market.” Almost two years on, New Zealand lags behind.

There’s two parts to this process. The first is the raw foundations, where the infrastructure is arranged so analysis can be conducted. The second is the ability to distribute AI-generated insight, and fully automated AI outcomes. We live in a digital world, where data is constantly created, streamed, modified and shared. The volume, velocity and complexity of all those data sources is simply too overwhelming for human cognitive ability. We get the machines to do the heavy-lifting in terms of data processing, analytics and intelligence gathering, so that the people in your organisation can focus on what really matters – the critical thinking.

Those data and AI outcomes will differ widely depending on what kind of business you’re in. But consider some early successes, for example in the medical field: accurately predicting patient bed numbers and cancelled visits. Or radiology, where AI can rapidly analyse X-ray or scans and accurately identify abnormalities, dramatically improving the ability to serve more people by making skilled doctors far more effective.

Our team has unearthed some fascinating insights using AI. For example, we worked with the Department of Conservation to turn raw recordings of kiwi calls into visual spectrograms. From there, we trained a machine learning algorithm to identify the calls in the images with high accuracy. This not only has a business efficiency benefit – it saves DOC scientists from thousands of hours of manual data coding – but has the potential to extrapolate out onto other datasets. If not the kiwi, then why not another endangered bird? Or could we flip it and use the model to identify predators?

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Capabilities like this are coming from machines which can learn from pattern identification. In fact, this pattern recognition is so good that there are systems capable of identifying if a person is male or female from a retinal scan – something humans themselves aren’t able to do. This demonstrates how far AI can go - and the raw material for learning, quite simply, is data.

Market readiness

I’ve mentioned the maturity of the BI market. The reality is that many companies are already spending enormous amounts on traditional data warehousing and analysis applications. What the expanded value proposition now on offer from Qrious means is that for the same investment it’s possible to benefit from a radically improved data platform. This is the next generation and thanks to cloud technologies, it means advanced analytics features with AI embedded.

Right now, the team is working with New Zealand businesses helping to migrate their data and workloads off traditional data warehouse environments and onto cloud-based data platforms. Every day we’re using migration tools like WhereScape RED or Redshift to build AWS or Snowflake datasets, overlaying cloud analytics and decisioning tools such as Tableau, Qlik or Power BI and helping clients experiment with the emerging AI and ML architectures and techniques.

It's imperative that New Zealand businesses are aware of this new wave of data-enablement. These capabilities are being brought to bear globally and AI is a bit like compounding interest - it’s hard to catch up once you fall behind. We’re seeing health, government, business in many other industries including tourism and retail, being transformed by data and AI.

So consider how this force will impact your industry now. And decide how your organisation will deliver value tomorrow.

Want to learn more about getting your data foundation ready for AI? Get in touch.

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