Google, Facebook, Apple and a host of other tech companies have come to dictate modern life. Whether we're shopping for groceries, posting pictures of our friends, or sharing financial data with a multibillion-dollar powerhouse, one could make the argument that becoming patrons of these tech giants is almost inevitable. But have recent scandals and controversies around some companies changed how the public views and uses their services?

Artificial intelligence can struggle with abstraction. The tools we depend on daily display a masterly command of details, but a shakier grasp of existential matters. Ask Alexa for a recipe, and she'll deliver it in seconds. Ask Siri about the meaning of life, and you'll get nothing more than a canned joke.

Data is a valuable asset – so much so that it’s the world’s most valuable resource. That makes understanding the different types of data – and the role of a data scientist – more important than ever. In the business world, more companies are trying to understand big numbers and what they can do with them.

The career opportunities for data scientists are constantly expanding. Advances in technology (e.g., 5G and IoT), along with the rapid growth of the profession itself, have encouraged data scientists to find new opportunities to flex their skills—and new ways to make a difference through their profession.

A momentous shift has occurred in the world of data analysis over the last ten years as the industry has turned its focus toward the digital arena. Once a sideline operation that was looked after by the IT department, data analytics is now front and centre in the strategic plans of every successful organisation. All signs point to this trend experiencing robust growth. A 2021 report produced by Allied Market Research projected the global big data and business analytics job market to grow at a compound annual growth rate (CAGR) of 13.5 per cent from 2021 to 2030.

The internet has completely reshaped how businesses operate. Throughout the world, we’ve seen the impact of technology on business, giving both consumers and businesses more flexibility. However, as technology advances, companies need to employ skilled technical staff to stay ahead of the curve.

Technology continues to evolve at an unprecedented rate and businesses need to be mindful of how these changes can affect their operations.

Businesses use analytics to explore and examine their data and then transform their findings into insights that ultimately help executives, managers and operational employees make better, more informed business decisions. Three key types of analytics businesses use are descriptive analytics, what has happened in a business; predictive analytics, what could happen; and prescriptive analytics, what should happen.

The magic of data, most believe, is in its ability to help us to predict the future. Rather than always looking backwards, data allows us to finally look forward, to plot the most likely pathway to success, In other words, data is all about predictive analytics.

But increasingly, business managers and data scientists are realising there is enormous value in using data to analyse past events. After all, until we clearly understand past patterns and trends, how can we possibly predict what might happen in the future?

Marketing departments in Australia and around the world are increasingly relying on the power of data science to capture consumer attention. While the creation of advertisements still relies on human creativity, tasks such as ad purchasing and customer targeting are data-driven and can be made more efficient by analytics and machine learning.

You’ve likely experienced the murkier side of data collection before. It’s commonplace for sites we’ve visited to show us advertisements further down the line, but what about connections that are a bit more tenuous

Perhaps your housemate is interested in a product and suddenly they’re targeting you as well. Or you get someone’s number and, without being linked to your phonebook, Facebook is suddenly suggesting them as someone “you might know”.