In this hyper-digital economy, we are creating more data every second than any time in history. The sheer volume of data is overwhelming, but there is gold in that data, valuable nuggets that can transform businesses and open up opportunities. Finding those nuggets takes an avid de-coder, someone with the expertise and innate curiosity that pushes them to dig deeper. It takes a Data Scientist.
Data is being generated at a break-neck pace; according to IBM 2.5 quintillion bytes (a quintillion is 1 plus 18 zeroes) of data are being created every day. Capgemini has predicted that the volume of data generated by businesses will increase 20,000-fold between 2000 and 2020. And these figures are only likely to grow as the Internet of Things and Artificial Intelligence become more pervasive and digital transformation projects gather steam.
The challenge this boom presents is twofold: the sheer volume of data is unprecedented. Firstly, 90% of the world's data has been created in the last two years and secondly, there is a significant skills gap in the area of data science.
Back in 2015 the European Commission (EC) looked into the data science skills gap and what it could mean for organisations. At the time, as many as 77% of data science and related jobs were unfilled and the EC expected that gap to widen further as demand for these jobs increases (160% increase in demand between 2013 and 2020, according to the EC). In total, the EC is suggesting that Europe will require almost 350,000 more Data Scientists by 2020 to fill the gap.
Data heavy industries like Finance, Insurance, Professional Services and IT are driving the demand for Data Scientists, accounting for 59% of the total job demand, according to a report by Burning Glass Technologies, Business-Higher Education Forum and IBM.
So what does a Data Scientist do that's so vital to these industries?
Let's think about the data that's being created. Our lives have essentially been digitised; connected devices from wearables to smartphones, online banking, shopping and dating. And let's not forget social media. How we interact with the world, each other and brands all generates bytes of data, information that could prove invaluable to organisations in making better business decisions.
The raw, unstructured data itself, while valuable, cannot reach its full potential without being processed into a usable format and analysed. Data Scientists are the wizards who can look at massive volumes of data and understand how to make sense of it. Without the expert insight and skills of a Data Scientist, organisations can be overwhelmed, they can miss key trends or opportunities, and worse still, they could misinterpret data and make poor business decisions.
The potential of correctly analysed the data is huge: McKinsey estimated that big data initiatives in the US healthcare system "could account for $300 billion to $450 billion in reduced health-care spending". On the other hand, bad data is estimated to be costing the US an eye-watering $3.1 trillion a year, according to IBM.
Even getting to the stage where data science can be applied is a challenge for most organisations: at the very beginning of an effective data strategy is its management. Collecting bad data at this stage could be costly in the long run. Next, organisations need to be stringent about how they store and secure all the data they collect. With the introduction of the EU General Data Protection Regulation (GDPR) in May 2018, there will be an increased emphasis on quality and security. Although GDPR is largely being seen as putting new restrictions on organisations and increasing the penalties they face for non-compliance, Gartner is quick to point out the opportunity that GDPR presents. "Don’t lose sight of the fact that implementing GDPR consent requirements is an opportunity for an organisation to acquire flexible rights to use and share data while maximising business value," says Lydia Clougherty Jones, research director at Gartner.
Aside from GDPR, organisations will need to implement advanced technologies to help compile all the data they are collecting, and present it in a usable format, and this is where the Data Scientists excel. They have an overview of all data, they apply processes and technologies to clean it, and then combine it into data sets which can be used to generate predictive models. This structured data, now simplified, can be used to develop business insights and better informed business decisions.
In their role, Data Scientists not only make sense of a massive volume of complex and often mind-boggling raw data, they use that data to find solutions to problems – whether it's organisational, societal, healthcare or climate change problems. The answers are in the data, and it's the Data Scientist's job to find them. They've been called wizards, super heroes and explorers, and the Harvard Business Review has called the Data Scientist, the "sexiest job of the 21st century". What's clear is as the volume of data we're generating continues to grow the role of the Data Scientist is likely to become more important for organisations looking to achieve a competitive advantage in the digital economy.
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