Is Data Science A Growing Industry in Australia?

Much can be said for data. It is in physical and digital form – and can be stored on the smallest of rocks and the largest of continental landmasses – yet, many organisations don’t yet know how to take advantage of the data that they have access to.

As Australia looks to rapidly transform into a high-tech economy, it’s wise to the role that data plays. After all, no matter whether you’ve studied data science postgraduate or are just beginning your first foray into data analytics, understanding how businesses utilise the data they have to get the most out of the rapidly growing data science industry in Australia can be incredibly advantageous when looking at your next role.

Data: The Transformative Impact on Modern Business

In the 21st century, much can be spoken of the transformative impact that technology has had on modern enterprise. As computers have developed, their ongoing integration into the workforce has led to remarkable changes in the way businesses operate. Roles that previously were considered irreplaceable, such as the roles of assistants and checkout operators have largely been replaced by automation and digital processes. The digital revolution is doing more to business than simply eliminating roles in workforces – it’s creating new operating channels and areas for businesses to innovate and improve their operations. 

Consider, for example, the rise of the online sales platform Amazon – from its beginning as an online bookseller in the 1990s, Amazon has used the power of data to transform business operations from simple customer insights to the global juggernaut it is today through the intelligent acquisition of platforms that provide enhancements to the existing insights that they have on customers. 

The Data-Driven Economy

Insights and data are incredibly powerful tools – and as technology has evolved, the ability to work with increasingly complicated and diverse sets of data has set a challenge for modern businesses. To succeed in today’s data-driven economy, you need to have the foresight as an organisation to embrace data and the insights it provides when it is appropriate.

For example, the 1998 acquisition of iMDB allowed Amazon to gain valuable insights into what titles were in demand at a given point in time. Over time, Amazon has sought to enhance the information that it has available to customers by developing or acquiring offerings that would provide real and meaningful information to their systems – whether it be the acquisition of media streaming platform Twitch, the purchase of grocery retailer Whole Foods, or the development of their own web services platforms.

While it may be an extreme case of the transformative impact that data can have, Jeff Bezos’ Amazon demonstrates the potential of data – more than just digits on a page, it can be used to innovate, educate, define, and shape entire economies in today’s day and age.

 

The Issues Faced By Data-Hungry Organisations

As businesses look to use data to drive their decision-making, it’s important that they consider the structures that may need to be in place to get the most out of your organisational data. Depending on how a business is structured, it may be necessary to invest in the development of new systems and enhanced problems.

Fundamentally, while it may seem like the problems of data can be categorised into three areas – velocity, variety, and volume, for the end user, contemplating the value of value in an organisation is also critical. To get the most out of data, businesses must invest in smart solutions – lest they make a costly mistake that hampers their ability to make the most out of data.

With some estimates expecting that global data usage will grow to approximately one billion terabytes annually, according to market research site Statista, there’s no doubt that data and its use will continue to play a transformational role in the modern workforce. Data professionals will be highly sought after, particularly for their capability to meaningfully capture insights in data and communicate them in a way that stakeholders can discern with ease.

 

Will AI Replace Data Science?

As data challenges continue to evolve in organisations, particularly in terms of volume and complexity, questions arise on just how viable the role of a data professional may be, particularly when platforms are releasing artificial intelligence (AI) and machine learning (ML) tools that can be used in manners that were previously unheard of. It’s reasonable to ask – if an organisation is implementing AI & ML solutions to replace data analytics capability in the workplace, will the data science roles be absorbed by automation as quickly as they are created?

The realm of data is complicated. Data presents unique challenges that are not always surpassable for robots – even if they can beat CAPTCHA codes. It seems unlikely that artificial intelligence will pose a threat to data scientists – in fact, it appears more of a possibility that businesses will support their existing teams with the use of supplemental tools such as Microsoft’s Copilot technology. The future of data is big, bold, and beautiful for the passionate and the brave – it’s an exciting time ahead in this rapidly evolving industry.

 

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