Deep Diving into Data Analytics | Study With New Zealand

It was his first job out of university that got New Zealand Excellence Award recipient Sagar Sanghvi so interested in mining nuggets of data gold from volumes of information.

While working in Bengaluru, India, for PromptCloud, a data analytics company, Sagar was fascinated by the staggering speed at which digital data was generated.

“It made me realise that data is going to be the next oil.

“We analysed data and turned it into valuable business intelligence for companies across a wide range of sectors – finance, e-commerce, travel and real estate.

“Deriving insights from text data is the need of the hour.”

Humongous volumes of data mean nothing until we refine them into usable intelligence, Sagar says.

Keen to deep dive into data analytics, Sagar decided to study in New Zealand after learning about the country’s robust contribution to data science. R, a statistical computing language used by data scientists worldwide, was developed by researchers/graduates from the University of Auckland, while Weka, a suite of machine learning software, was developed at the University of Waikato.

New Zealand’s membership of the Digital 9 (D9), a network of the world’s most advanced digital nations, further strengthened his decision to study in New Zealand.

“I also had a good friend enrolled in the Master of Analytics programme at AUT, so had lots of discussion with him about the course and future job opportunities.

“It was a good decision,” he says.

Sagar loves how his master’s programme blends theoretical concepts of data analytics with its practical applications, making the students industry ready when they graduate.

"The courses are structured in a way that [you] become an expert with core papers and a generalist on a wide range of elective subjects."

“This helps to future proof yourself as becoming a ‘master generalist’, which is a vital ingredient in today’s job market.”

In late 2018, Sagar started an internship at IntelaAI, a Wellington-based data analytics company specialising in machine learning, particularly, natural language processing, which is about helping machines build a nuanced understanding of human language and speech. It does this by teaching them how a sentence’s grammatical meaning can differ from its colloquial, everyday usage.

“Take this line for example – ‘Shah Rukh Khan set the stage on fire’. As humans, we know that is an expression meaning he is a great performer, but a machine would take this literally, and the results would be comical.”

As an intern, Sagar’s work is focused on natural language processing projects. He says his lecturers have played a key role in helping him to develop strong industry-relevant skills that he is able to apply to these projects.

Sagar’s AUT project supervisor Dr. Mahsa Mohaghegh’s research work on machine learning for English and te reo Māori (New Zealand’s indigenous language), for example, is informing his work on a natural language processing project for te reo Māori.

“I am grateful for Dr. Mahsa’s guidance on natural language processing for te reo Māori and the way in which I am able to directly apply my classroom learnings to work projects,” he says.

The course’s practical, hands-on teaching style has also influenced Sagar to think and learn in newer ways. For example, every week, the university invites a speaker from the data science industry to share their insights about working on real-world projects, he says.

“The sessions help broaden your perspective; you can associate practically what you are learning theoretically; the learning also continues outside the classroom as New Zealand has a small but extremely active tech community with regular meet-ups, conferences and hackathons.”