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Many new industries have boomed since our lives became completely intertwined with digital products, but few are as surprisingly diverse as analytics. The field might still be in its infancy, but the future is bright for graduates in this area. Many of the best companies in the world are producing huge volumes of data, so being able to wrangle and interpret it is extremely valuable. So where can studying data take you? Deakin University data analytics Director of Teaching Dr Dilal Saundage shares some of the best opportunities for those who’d like a career mining data.
Data scientist roles are among the most coveted, but also require the most sophisticated computer science skills. According to Dr Saundage data scientists can expect to earn a salary of between $180,000 and $200,000 per year. ‘Companies hiring data scientists have massive unstructured data sets – for example, Telstra, Optus and insurance companies,’ he says. Social networking sites also have a huge demand for people who can interpret the data that is collected from user activity.
This data might be then used to assess usage patterns or to inform new products to enhance a user’s experience. For example, data analysis might show that women over 30 are most likely to buy insurance in January, so new products would be targeted to their needs at that time of year. But when the volume of data is huge, the job becomes complex. ‘It’s like digging for gold. They are looking for insights in massive data. It can take months to work out if there’s something they can use,’ Dr Saundage explains. When you consider the data in a network such as Instagram, where users have posted more than 40 billion images and now share around 95 million photos and videos every day, there’s an abundance of information for data scientists to dissect. Distilling the activity into something meaningful requires patience and skill.
'Companies hiring data scientists have massive unstructured data sets – for example, Telstra, Optus and insurance companies.'Dr Dilal Saundage,
Deakin Business School, Deakin University
Advanced analytics professionals also interrogate details, but unlike data scientists ‘they try to predict some events or outcomes, for example, what kind of customers might leave a business,’ Dr Saundage explains. ‘They’re more traditional problem solvers,’ he adds. This is particularly valuable in areas such as retail, where customers are spoilt for choice. Being able to understand a customer’s behaviour and purchase history at extremely detailed levels means smart companies can know what their customer wants – and give it to them – before a competitor does.
For example, retailers that perform in-depth analysis of buying patterns might be able to predict which stores will run out of a popular item and when, then avoid that item going out of stock, providing a better shopping experience and increasing sales.
A big plus for people who want to work in data is that there are opportunities in almost every industry. In particular, Dr Saundage highlights a need for business analysts and demand planners across all sectors. In the education sector, analysts might look at how to improve internal processes or track staff retention rates. While in the transport industry, ‘demand planners do the optimisation. They find out what the fastest route is in order to save the company money’. In fact, every sector is hiring, he says. So choose a subject you’re passionate about and explore the analytics opportunities within it. For example, music lovers would be hard pressed to find a better company than Spotify, where analysts use listener insights to improve the offering and experience of using Spotify. Plus there’s a house band and plenty of perks.
From mining to government, companies are learning how to use data to their advantage. ‘If a company has data, they want to know how best to use it,’ Dr Saundage concludes. So graduates have the luxury of setting their sights on any company they aspire to work with, and build what promises to be a flourishing career.
Love data? Consider studying business analytics or data analytics at Deakin University.
Director of Teaching, Deakin Business School, Deakin University
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