The emergence of big data has led to the creation of a new profession known as a data scientist, but the main problem with this new line of work — which involves a combination of skills made up of statistics, coding, and business consultancy — is that it's currently a rare profession, according to Qrious general manager Cyrus Facciano.
To address this challenge and to build up the data science skill base within New Zealand, Qrious is establishing a Data Science Academy, which is due to open in a few weeks, where students and professionals will be trained, tutored, and tested on their knowledge of these new techniques over a 17 week course.
"Talent is a major problem. When we were doing our initial analysis and using the studies around data scientists and the global shortage, we estimated there'd be about 1,200 data scientists short in New Zealand in the next three years," he said.
"We had a look around and we saw there was one university offering it, but there were a total of six pupils, so we figured there's a major limit with realising that value."
The first initiative that will be offered at the academy will be a data training science program, with plans set on shortly introducing an application program, which will look at techniques and languages to help with the development new applications.
Facciano said while it will be an intensive program, programmers are already half way to becoming data scientists as they are "already really good at coding and now it's just learning about statistics and use cases of how it's going to have an effect on a business".
The launch comes off the back of New Zealand Telecom Digital Ventures announcing the establishment of Qrious, a standalone startup, which aims to help businesses and organisations within segments, such as government, healthcare, public transport, and housing, to use available data sets to improve their products and services.
Facciano said during the, which started mid-last year, it became obvious there was a situation where there were a lot of duplication of efforts and inefficiencies in the way businesses analysed and leveraged data. This led the company to look at how they were going to establish an ecosystem or data hub that would enable for all the data that existed in the country to live in a centralised location.
As a result, Qrious partnered up with Pivotal, an EMC-owned subsidiary that is backed by investments from VMware and GE, for its enterprise platform-as-a-service product, Cloud Foundry.
"In a talent starved industry, you need to be able to draw talent from everywhere so you have to have a platform where customers can setup projects and bring in capabilities from both local and global places. Kaggle is a good example of how data science collaboration is drawn from all over the world to solve problems," Facciano said.
Pivotal president and head of products Scott Yara said the concept behind Cloud Foundry, which is supported by companies including IBM, SAP, HP, Intel, and Rackspace is about "living in a world of many clouds" and allowing any application to run on any cloud platform, rather than just having the "unfortunate circumstance where ... there is one cloud for the whole world and it was just Jeff Bezos'".
Yara continued saying that Cloud Foundry is to Amazon what Android is to Apple.
"We look at Amazon and the success they've had, but it's a very vertically integrated cloud computing model, where it's their data centres, their machines, their software, and their services," he said.
"It's much like how we look at Apple in the world of mobile where they had a very integrated model. Then Android came about and created an open ecosystem alternative in the world of mobile."
Pivotal has continued its goal to enable data driven enterprises to leverage the cloud with the announcement of its Big Data Suite, an annual subscription based service that bundles access to a pool of its products.
Yara said the suite fills a much-needed gap in the market, helping enterprise companies to capitalise on explosive data growth by offering a multi-faceted data portfolio with a "use it as you need it" pricing model.