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The data science workforce is forecasted to grow by almost 16 per cent by 2025*. Organisations around the world are learning to unlock the value of data to stay innovative and competitive in the market. As a result, demand for professionals with strong data management, IT and analytical skills is expected to soar - but the industry is experiencing a significant skills shortage, and employers are struggling to keep up with demand.

Now is the time to equip yourself with a powerful skill set that will have a huge impact on your employability now and into the future. Discover the top skills that IT professionals and data analysts need to succeed in the sector.

* Employment Outlook to November 2025, Australian Government Department of Employment.


Top skills employers look for in IT professionals and data analysts

  1. Big data and data science – transform data into meaningful insights to achieve business objectives
  2. Technical programming and coding skills, attention to detail
  3. The ability to integrate technical expertise with broader business acumen
  4. Project management skills – ensure projects finish on time, adhere to budget constraints and meet quality standards
  5. Adopt an innovative design thinking mindset to come up with creative solutions

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Discover the essential skills IT & data analytics professionals need to succeed, career opportunities, and industry trends in your free 20-page career guide


Jobs for IT professionals and data analysts

Technology is reshaping the workforce, redefining jobs, and creating new roles never seen before. The explosion in device connectivity, increasing data volumes, combined with the rise of the Internet of Things and the impact of social media are all factors that will fuel exponential growth in IT and big data in the future. Professionals in this industry are well sought after by businesses in non-IT sectors, in areas like finance, accounting, insurance, healthcare, marketing, and professional services.


Big data visualiser

Big data visualisers use visualisation tools and software to communicate information in different ways; present data in a way that is easy to understand, and spot patterns, trends and correlations. Big data visualisers combine data sets across multiple sources; and deliver data in a useful and appealing way to users.


Data scientist

Data scientists understand interfaces, data migrations, big data and databases; take the lead in processing raw data and determine the best types of analysis; mine large volumes of data to understand user behaviours and interactions, and communicate data findings to IT leadership and business leaders to promote innovation.


Business data analyst

Business data analysts work with stakeholders, analysts and senior management to understand business strategy and the questions that need to be asked; identify research needs; design experiments and make recommendations based on results; drive complex analytics projects to support the business.


Web and software developer

Web and software developers code, test and debug software applications; interpret customer requirements; work with a team to research, design, and write software; and work with others to understand and resolve issues in existing software.


Database designer

Database designers design stable and reliable databases; develop, test, improve and maintain new and existing databases to help users retrieve data effectively; and work closely with developers to ensure system consistency.


Chief data officer

Chief data officers lead the data and analytics priorities for an organisation; manage data as a strategic asset and operationalise data governance, data quality and other controls to sustain the integrity of data; and identify business opportunities through data.


Chief analytics officer

Chief analytics officers assess the most effective operating model and data approach to achieve business objectives; define and drive the enterprise-wide analytics vision across strategy, people, data and technology; and be heavily involved in business transformation, and education needed to embed analytics into the organisational culture.


data engineer

Data engineers develop, construct, test and maintain architectures such as databases and large-scale processing systems; gather, process and transform raw data from different sources and third parties; and extract data from systems to develop insights and make business decisions.

Looking to change your career?

If you’re fascinated by new emerging digital technologies and the world of big data, a career in IT and data analytics can be an extremely rewarding profession. But how do you become a data analyst, an IT professional, or any of the other roles this industry has to offer?

Studying online is a great way to build the knowledge and skills that employers are looking for while giving you the flexibility to continue working while you study. It’s never too late to pursue your passion.

Take the first step with our IT or a Data Analytics degree.

Want to move up in your current role?

You may currently be working in IT-related roles and wish to gain experience in data analytics to enhance your career prospects. Or perhaps you work in a completely different industry where there is a strong demand for IT and data analytical skills. Studying online and gaining a qualification is a perfect opportunity to complement your work experience and expertise, and take the next step in your career.

This degree is highly recommended for people currently working in roles like:

  • Database and systems administrator
  • Data analyst
  • ICT support technician
  • Software and application programmers/developer
  • Computer network professional
  • Computer systems analyst
  • IT Help Desk Technician
  • UX and website designer
  • Mobile application developer

Whether you’re looking to upskill and advance your current career or embark on a career change, UniSA Online’s IT or a Data Analytics degree will give you the skills to help you achieve your goals.

Study IT and Data Analytics 100% online

Gain a solid IT foundation and develop expertise in data analytics. Learn to analyse and visualise rich data sources, sport data trends and generate data management strategies using industry-standard software tools.

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