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How advances in data and analytics are changing the world of work

Big changes are happening in the world of data. Incrementally, year-on-year we’re seeing a shift in perceptions, processes and people’s skills and experience. As technology advances, it’s leading directly to changes in data science and analysis. These developments have begun to allow us greater access to raw data, offer us better and faster ways to uncover insights and give a wider range of people the opportunity to analyse the data at their fingertips. With this growth, comes a shift in the types of roles and experience needed to work in data science. Let’s take a look at what’s been happening and how it’s going to affect the jobs of the future.

New sources of data

The popularity of the internet of things (IoT) has given rise to an enormous amount of extra data that businesses are now able to gather and harness insight from. With IoT only set to continue growing, we expect the amount of data to increase each year too. Having such huge amounts of data also gives rise to increased amounts of Dark Data. Of the amount of data collected by businesses it’s estimated that 65% of it is hidden and unused. This too could be a newly tapped source of insight and value in the near future, as we create new ways to tap into and process the data we have available.

Quicker results and more context

We’re about to see a new age of quantum computing which will allow for faster processing and will help us to solve problems that we haven’t been able to even consider with our existing computers. The growth of Artificial Intelligence (AI) has also allowed us to automate processes and improve efficiency. And, as machine learning and predictive analytics develop further, we’ll be able to uncover not just what’s been happening but what might happen in the future too. As an additional bonus, because there are now prebuilt AI applications available on the market, it’s also a technology that’s available to both big and small business alike, which brings us onto our third area of advancement.

Increased access

Let’s start with open source solutions. There is a growing number of programmes and solutions now on the market which are open source and available for modification by developers. This creates a much cheaper option for businesses looking to invest in analytics and opens up the world of data processing to a much wider range of businesses. Then we have edge computing. By moving data processing closer to IoT devices and sensors, and away from the cloud, we can reduce the cost implications of using cloud services and improve performance, with less data needing to be transmitted at any one time. All this technology doesn’t come without risks however, and if the recent data breaches of the past few years are anything to go by, security is a top priority in the data sector. Again, better security will allow for greater access to platforms, for businesses that might otherwise choose the safer route.

The future of data roles

So where does that leave us? As the amount of data available gradually increases, we’re going to see an ever increasing demand for people who understand data. Even for those not working directly with data, an understanding of STEM fields will become more and more necessary. We are likely to also see a rise in the demand for hybrid roles, where analytical skills are needed alongside experience of a certain sector, for example HR roles which need to take on analysis of employee data.

The biggest change we hope to see in the future, is that of the further clarification of job role names. Until now, there has been a huge demand for ‘data scientists’, a very generalised name for a wide range of skills. Now with the impact of the new technologies we’ve discussed and the growth in the range of skills and experience needed, it will be essential for businesses to tailor job titles around specific areas like machine learning, data engineering, research and beyond.

Read our related blog: Augmented reality: how will it affect our work space?

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