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Aussie tech start-up set to redefine $320 billion big data industry

March 9, 2022

Aussie tech start-up set to redefine $320 billion big data industry

Skyrocketing demand for big data has created both a global industry valued at $320 billion and a global problem of equal proportions: Current platforms are struggling to handle the weight of centralised data sets, to the point it is predicted to be overwhelmed and obsolete by 2025.

Skyrocketing demand for big data has created both a global industry valued at $320 billion and a global problem of equal proportions: Current platforms are struggling to handle the weight of centralised data sets, to the point it is predicted to be overwhelmed and obsolete by 2025.

With this potential time bomb ticking down, the massive and largely unprepared market is on the cusp of being forced into a new era – and Zetaris is ready to lead it through the change.

The Australian tech company has developed the fastest big data analytics program in the world – a next-generation data analytics platform that uses first-to-market data mesh technology to enable businesses to generate insights without centralising their data sets, leading to cheaper and more accurate results.

Despite Zetaris only recently emerging from stealth mode after a lengthy period developing its state-of-the-art solution, it has already signed contracts with major enterprises such as Bupa, Optus, Nokia, Melbourne Water, Telstra, NBN and The Murdoch Children’s Research Institute, and has pilots commencing with US, Canadian and South-East Asian customers.

The company has also attracted the attention of major tech businesses, with both IBM and Microsoft forming partnerships with the start-up as it gathers pace. Meanwhile, US government-backed venture capital fund In-Q-Tel, which invests in businesses it believes are important to national security, has already taken a stake in Zetaris.

Modern businesses rely on big data to optimise their operations and gain a competitive edge over rivals, but a study by consultancy firm Gartner found 85% of big data projects will end in failure. These failures are the product of biases within the data being used, problems with algorithms, and issues within the human teams managing these massive undertakings.

Separate research by Experian showed weakness in big data analytics prevented a majority of businesses from adequately responding to the challenges posed by COVID-19, and hindered their ability to improve customer experience.

These failed projects are costing businesses, with potentially months or years of labour and millions of dollars squandered.

On the flip side, businesses that have effectively utilised big data have seen initial profit increases of 6% after taking advantage of the vast pools of information they had collected, according to research by McKinsey.

This figure grows to 9% after five years leveraging big data analytics, or as McKinsey noted: “Big data investments amounted to 0.6% of corporate revenues and returned a multiple of 1.4 times that level of investment, increasing to two times over five years.”

Industry prepares for new era

When computers first started to become a standard part of the modern office in the 1980s and ’90s, major businesses like Microsoft and Oracle duked it out for a share of the immense new data market.

As computing power advanced and client needs shifted, these businesses were left vulnerable to disruption, and sure enough new businesses – notably Snowflake, which launched in 2014 – emerged to reshape the way the market operated.

When Snowflake – a cloud-based data warehousing outfit from Silicon Valley – floated on the the NYSE in September 2020, it was the largest software IPO in US history, and attracted numerous notable investors, including Warren Buffett’s Berkshire Hathaway.

But progress within the technology industry doesn’t stop, and businesses like Snowflake now face their own existential reckoning with the emergence of data mesh technology.

The problem? Data is becoming too big. The volume of data being generated by the average person has grown rapidly and is expected to keep growing, a process only accelerated by the rollout of 5G technology.

*Data sourced from Seed Scientific

By 2025, the sheer volume of data being collected and stored will be too large for enterprises to centralise, creating a significant problem for data warehousing businesses, like Snowflake, which bring data from different sources together in one place before processing it.

Zetaris has developed the next generation of big data analytics platforms, leveraging first-to-market data mesh technology that enables businesses to process and analyse information without centralising the data first.

Instead, Zetaris’s platform stitches the data together in real-time using the company’s unique ‘heterogeneous query optimiser’. Think of it like a brain sitting across an enterprise’s numerous individual data sets and silos. 

Once integrated with a client’s data sets, it knows where individual pieces of information are stored and can automatically write code to take a user’s query to the relevant data, rather than duplicating the data into a centralised platform for analysis.

 

For end-users, this means big data queries can be undertaken and insights generated within days or hours, rather than weeks or months – all the while eliminating the risk of duplication errors undermining data quality.

As the volume of data being collected begins to exceed the limits of what centralised platforms can handle, Zetaris’s unique networked data platform is ideally placed to help businesses achieve their big data analytics aspirations. 

CEO and founder Vinay Samuel has an extensive 20-year history growing and selling businesses, with the cumulative value of his exits worth roughly $1.2 billion so far. He and his team have successfully commercialised the Zetaris platform while building it, and have now exited stealth mode with proven technology relied on by major global enterprises.

This team includes board director Robert McLean, a former Fullbright scholar whose career includes 26 years helping consulting giant McKinsey grow its Australian operations, leading some of the nation’s largest organisations through periods of immense change, and serving on the Reserve Bank’s Payments Systems Board.

Standard Chartered COO David Whiteing, the former chief information officer for Commonwealth Bank, provides additional support in his role as non-executive director.

Zetaris’s executive team also includes chief revenue officer Paul Cikala, whose 30 years in the industry has seen him lead large-scale information management, analytics and AI domains teams and projects; and chief data officer Dr John Brudenell, a former director at UTelco Systems, where he spent roughly 15 years providing specialist consultancy services in business transformation, data modelling, enterprise data warehousing and master data management.

Zetaris is now primed for growth, and Reach Markets is offering wholesale investors the opportunity to invest in this business alongside institutions at this critical phase in Zetaris’s expansion. The company has already received offers from competitors but with the stage set for rapid expansion Zetaris intends to seize the growth opportunity in front of it.

The company is currently raising funds to fuel its global expansion, with a particular view to breaking into the North American market.

We have already received substantial interest in this wholesale opportunity and don’t expect the offer to be open for long.

Join our live investor briefing with Vinay Samuel today, at 1pm (AEDT). Click here to book your spot. 

Past performance is not a reliable indicator of future performance and you should read the offer documents in full when they are available before making any decision on this investment. Any advice is general only and does not consider your objectives, financial situation or needs, and you should consider whether it’s appropriate for you.

Reach* are the advisers assisting with the management of this offer and may receive fees depending on whether an offer is taken up by investors.

Sources


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