This has been the year that big data has become, if possible, even bigger. A survey by Gartner found that 48% of companies invested in big data in 2016, and nearly three quarters of those surveyed have already invested, or plan to invest.
And this trend looks set to continue. Decisions are being driven by data in many different sectors, from marketing and pharmaceutical companies to third-sector organisations. Algorithms within the advertising industry are influenced by information about shopping habits, and the same data-driven algorithm is used for engineering both Formula 1 vehicles and asthma drugs.
But just how far can big data take us? Has it reached its peak or is there more potential to explore? We’ve had a think about what 2017 means for big data.
1. There will be more data
Perhaps the most obvious big data prediction for the upcoming year is that there will be more of it. The increasing number of individuals living their day-to-day lives largely through the internet means that there is more opportunity than ever before to create and collect data, and by 2020 the amount of data that is worth analysing is predicted to double.
Everything from social media, health monitors and taxi apps collect data from the user, all with the aim to improve and personalise the user experience and make more efficient, cost-effective business decisions.
Recently, British Airways put out a patent application for a ‘Digital Pill’ – a system which intends to personalise the travel environment for each passenger. It would work as an ingestible sensor and would supposedly monitor temperature, sleep phase, and heart rate. This data would then be fed to the airline which would then alter elements of the individual’s in-flight experience, such as their meals, sleep-times, lighting, and in-flight entertainment, accordingly.
This revelation shows just how advanced the use of data can get, and raises the question of what other innovations we will see emerge in 2017 that we had previously thought to be impossible.
2. There will be more demand for big data and analytical skills
Businesses should get big data analytics on their list of new year’s resolutions if they want to provide a better service to their customers and keep their competitive edge. Personalisation has become ordinary for consumers, who now expect businesses to go a step further. For example, users of TV and film subscription services such as Netflix assume that the app will understand what they’re looking for and recommend shows for them to watch. Businesses should use data to make the customer’s journey more efficient and convenient, something that traditional data, such as demographics and credit scores, can struggle to achieve.
A significant benefit of big data is that it encompasses a large number of data points from a range of sources, and can therefore paint a much more accurate picture of an individual consumer at one point in time than businesses could have dreamed of ten years ago.
It allows companies to verify identity and detect fraud, and provides insight and predictions into behaviour like travel, outings, and vote outcomes. It could even save lives – researchers have discovered a way of utilising machine learning to develop predictive models for the onset of type two diabetes.
This demand will subsequently lead to businesses needing to recruit staff with big data analytics skill sets, or work with an external specialist to keep up with industry competition and customer expectations. This may mean a rise in people with jobs like data scientists, data modellers, data analysts, developers and more.
3. There will be more monetisation
Plenty of experts have predicted that the creation of this data and its use will result in its monetisation. The chief executive of Dell, Michael Dell, has predicted that big data analytics is the next trillion-dollar market. IDC predicts that that data monetisation efforts will result in enterprises increasing the marketplace’s consumption of their own data by 100-fold – or even more.
By 2020, the amount of data that is worth analysing will double. Forrester expects that as firms will try to sell their data, ‘many will sputter’, but in 2017, an increasing number of firms will look to drive value and revenue from their ‘exhaust fumes’. Forrester declares that ‘all companies are in the data business now’.
The trouble comes with identifying which type of data is useful – but it seems that businesses aren’t too far away from achieving this. IDC predicts that by 2020, organisations that are able to analyse all relevant data and deliver actionable information will achieve an extra $430 billion in productivity benefits over their less analytically oriented peers.
Although this is a good few years away, we are likely to see a move towards this in 2017, as a similar figure for revenues associated with data monetisation would get us closer to Michael Dell’s trillion-dollar prediction. In the same interview, Dell described the current state of data analytics, saying that: ‘If you look at companies today, most of them are not very good at using the data they have to make better decisions in real time’. However, as the big data market continues to grow, we are likely to see companies making better business decisions as a consequence.
4. There will be a deviation away from the buzzword
‘Big data’ has been one of the biggest buzzwords of the last couple of years, but as its use grows, this term will be used less. Big data itself is raw and unstructured, making it near impossible to derive meaning from it without implementing tools that are capable of analysing it and creating meaningful insights.
However, we have already started to see move away from the ambiguity of the term ‘big data’. Terms such as ‘smart data’ and ‘actionable data’ differentiate between the offerings of the different types of analytical tools available.
Ultimately, it looks like big data is here to stay in 2017. Data analytics has gone a long way towards transforming almost every sector this year, and patents for innovative products, huge growth in the amount of data generated, and increasing customer demand mean that data will likely be the driving force behind many business decisions next year.
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