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Society’s ever-increasing reliance on technology is creating an unprecedented amount of data to be interpreted. Whether it’s messages, reviews, photos, medical information, internet searches or product and service performance, most companies will have access to some form of unique data. This means specialists who can wrangle big data are in high demand: enter the much sought-after data scientist.
Dr Simon James, a Senior Lecturer in Mathematics at Deakin University, says making sense of data has become a primary focus in the field of information technology. ‘We have a lot of data available to us but it’s useless unless we can extract meaning from it. Studying data science is about learning the tools for extracting meaning from data and learning what data can do.’
Data scientists have a unique set of problem solving skills that other professionals may lack, Dr James explains. ‘A lot of organisations are realising that they need to tap into this potential and so they are either hiring data scientists or upskilling their staff.’
Professor Maia Angelova Turkedjieva, a Professor of Data Analytics and Machine Learning, believes that the abundance and variety of data has created a new frontier. ‘Data scientists can improve processes, access market information or predict company behaviour,’ she says.
‘They can gain information about the competitors and gain advantage in the market space. Using data performance for future advertising and decision-making can optimise a company’s performance.’
One of the primary signs that data scientists are being increasingly valued is the senior advisory roles that they are taking on. ‘Data scientists are being trusted with new responsibilities within organisations,’ Dr James says. ‘They are being trusted to drive decisions and innovations.’
Like many other fields, automation is making certain roles in data analysis obsolete while other roles are becoming more sophisticated and demanding. ‘Simple data analysis used to be a job in itself but now it’s done so easily with the tools that are available,’ Dr James says. ‘Companies don’t need people in those roles any more but what they do need is people who are creative and have the cognitive skills to adapt and drive things that can’t be done by automation.’
According to Dr Sutharshan Rajasegarar, a Senior Lecturer in Computer Science, data scientists are encouraged to understand the limitations of the techniques they’ve been taught so they are prepared for future advances. ‘They are taught to extend their knowledge beyond what they have learned so that if new techniques are coming up they will know how to utilise their skills to understand and use these techniques within their organisation.’
'Data scientists can improve processes, access market information or predict company behaviour.'Prof. Maia Angelova Turkedjieva,
School of Information Technology, Deakin University
One vital role of data scientists is providing insights on resource optimisation. ‘They can advise companies on how to effectively use existing resources to minimise the cost, improve productivity and give them an edge over their competition,’ Dr Rajasegarar says. ‘Some examples include advertising campaigns, new product planning, using intelligence about competition and informed decision making.’
While gaining insights about the products and processes in the company they also look at patterns in customer behaviour, customer satisfaction and also social behaviour around different products. As Prof. Angelova Turkedjieva explains, ‘this allows them to inform the company about the steps that they need to take to improve future performance and to gain advantage over competitors.’
Communicating data insights
Prof. Angelova Turkedjieva says you can’t really consider data science on its own. ‘It is an interdisciplinary science which pulls skills and abilities from statistics, from IT, mathematics, business and engineering. The soft skills in terms of communication, visualisation and data presentation are also essential.’
Dr Rajasegarar agrees: ‘we not only teach the students how to elicit, analyse and interpret data, we also teach them how to present and demonstrate this to different audiences whether that is at the managerial level or to other data scientists. It’s important to make the assumptions and limitations also interpretable so it is understandable to anyone.’
‘It comes down to trust and communication between data scientists and the company that they are working for,’ Dr James adds. ‘Data science communication is absolutely essential so that you can form teams where the expertise that the data scientists have can be capitalised on in a big way. They need to be able to communicate with people so the stakeholders understand what they can do and so that everyone’s expertise can be combined.’
These skills give graduates an advantage when they are looking to move up in an organisation. ‘Soft skills such as the ability to lead and communicate are always going to be essential no matter what industry you are in if you wish to move into more senior roles,’ Dr James says.
Explore your opportunities for a future in big data with the Deakin Master of Data Science.
Senior Lecturer in Mathematics, School of Information Technology, Deakin University
Professor Of Data Analytics And Machine Learning, School of Information Technology, Deakin University
Senior Lecturer in Computer Science, School of Information Technology, Deakin University
