Home' Forge : Vol 2 No 2 Contents Zetaris
Big data analytics company Zetaris, which
was founded in 2012, has done something
that most young companies can only dream
of. In 2014, Westpac Bank, through its
venture capital fund Reinventure Group,
took an equity stake in the company.
Westpac had been a client of Zetaris.
Vinay Samuel, founder and chief
executive of Zetaris, says the investment
changed the company's approach. 'We
can truly look at tier-one opportunities,
and they [Reinventure] can have
confdence in us,’ he says. ‘The risk of
being a small business has gone away.
It has transformed our business and
transformed our opportunities. We can
now take on the globe -- in the United
States and the United Kingdom.'
Samuel says a point of difference with
Zetaris is that the solutions offered do not
require the clients to make heavy internal
investments. 'We developed a new type
of platform that handles structured and
unstructured data,' he says. 'It enables
businesses to use powerful data products
without the need for deep-coding
capabilities. IT just supports the platform.
'You don't have to bring the data to us.
You can just give us your query, and we
can go to the systems and only bring
back the answer. It saves lots of time, and
typically we are about one-third of the
price because of the way that we do it.'
Samuel says the private equity frm Exto
Partners has also bought a stake in the
business. He believes that there is a lot
more activity in the big data space in
'In the last 18 to 24 months, there have
been a lot of attempts to build big data
capabilities using open-source platforms.
But often the expectations haven't been
met. There is a fair bit of disillusionment.'
Alexander Brown, a partner at data consultancy frm Analytics8,
believes that Australian businesses have been 'conservative and
pragmatic in their adoption of big data technologies'. He says
there is considerable interest in big data and the opportunities
it offers, but Australian businesses are more averse to the
technological risk than those in the United States.
'With a smaller population and market, many Australian
businesses are simply not generating the volumes of data that
make big data tools so appealing elsewhere,' he says.
The most advanced sectors in Australia, says Brown, are
banking and telecommunications. 'Companies in these sectors
were already creating, managing and analysing huge volumes
of data. They have the scale, the capacity and the business
need -- such as reducing the costs of analytical solutions -- to
invest in cutting-edge, but often immature and development-
Brown believes that companies usually understand that big
data technologies are just enablers for their business strategy.
The risk, which is not unique to big data, is that companies
focus on the underlying technologies, rather than the
opportunities that they provide.
'In an ideal world, companies would develop a strategy for
data collection that aligns available data sources with short- and
long-term needs, and opportunities to be better at what they do.
Part of that strategy is understanding the cultural changes and
skills required to become data-driven, and the use of data and
analytics in an organisation's decision-making processes.
'In practice, there's a risk that cheap storage and big data
technologies are used to create data lakes or possibly data
landflls – vast, uncharted repositories of data that organisations
have neither the skills nor the business need to analyse.'
Analytics8 was founded in 2002. It has 45 employees in Australia
and 100 in America. The company designs and builds systems
and has teams dedicated to advanced analytics and emerging
technologies. 'The analytics team focuses on the "what" of big
data: statistical models, predictive analytics and machine learning
that allow organisations to use data in a proactive way.
'Our emerging technology team focuses on the "how" -- using a
range of technologies to best implement big data projects. That
team is also tasked with understanding the rapidly evolving
big data technology sector, and providing strategic advice to
our clients about the best and most appropriate technologies for
'Huge volumes of data create a new problem: there's simply too
much of it for people to analyse or use it in a meaningful way.
Even today, there's an acute shortage of statisticians and 'data
scientists' with skills in data analysis. The next 10 years is going
to be about the development and use of sophisticated machine-
learning technologies to support, and possibly replace, people in
the analytical process.'
cover story // 25
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