Organisations have long used data analytics to inform their strategies but, with the rise of big data, they now lack the skills necessary to harness the full depth of insights it can provide. This is due to the sheer volume of data being generated every day, and the complexity of interpreting it all. These insights enable better decision making on everything from solving societal difficulties and improving consumer quality of life, to responding to humanitarian crises and guiding defence and security.
Being able to dive into this data and understand which parts matter most is a skill growing rapidly in demand. Data scientists are the talented individuals tasked with understanding big data and identifying its insights for organisations.
Their highly specialised skills include coding, statistics, mathematics, data visualisation, computer science, and data mining. To aid in filtering the wealth of data available, they develop AI and machine learning algorithms. The years of study to develop these skills, means the demand (opens in new tab) for data scientists will have outpaced supply by 50 per cent by 2018. Data scientists have already improved our lives and made them more comfortable. Their work means we can interact with big data through our devices, telling us where to eat, which films to watch (opens in new tab), and the fastest travel routes (opens in new tab), at the touch of a button. But what’s more interesting are the ways data scientists are leveraging big data across the humanitarian and defence sectors.
Dedicating data to defence and humanity
With an untold number of crises emerging every year, big data is becoming increasingly important for helping aid organisations respond quickly to chaotic and evolving situations. By finding patterns in data provided from connected devices and private sources, data scientists can use computer algorithms and analytics to provide a deeper and quicker understanding of emergencies.
You only have to look as far as Sweden’s Migration Board (opens in new tab). During the 2015 refugee crisis it saw an increase from 2,500 asylum seekers in a month, to 10,000 per week. The agency managed the intake by starting the process of procuring housing early, hiring extra staff and preparing supplies, despite its sudden intake. This is because the Swedish Migration Board had already been using big data and analytics for several years, and predicted the increase. This prediction helped it prepare for the crisis in a way other organisations may have struggled to deal with.
Despite the clear benefits of data science, there are obstacles which stand in the way of achieving these results. Data scientists may struggle to acquire the necessary resources, whether that involves recognising the best technologies for their needs, or finding the funds to pay for the talent and technology. They could also have difficulty gaining access to relevant information to analyse. Thankfully, the launch of open data initiatives (opens in new tab), aimed at removing the barriers to useful data for organisations, has improved this in recent years. Many data scientists have only had the opportunity to apply their skills to business and technology use cases, and may not have experience in sectors beyond these.
Testing data science in the real world
Aiming to test the talents of data scientists by developing new approaches to real and complex problems, the Defence Science and Technology Laboratory (Dstl) and other government partners have launched the Data Science Challenge (opens in new tab). Part of a wider programme set out in the Defence Innovation Initiative, the challenge acknowledges that often the best minds aren’t necessarily the ones that work for you. It’s open to entrants of all data science specialisations and backgrounds.
The challenge is broken into two tests:
- The first involves creating a means of detecting and classifying vehicles such as cars, motorbikes and buses, from a selection of aerial imagery. This solution could be used, as an example, to facilitate safe journeys of vehicles through conflict zones.
- The other test assesses a data scientist’s skill at analysing data found in documents such as media reports. This could help provide a better understanding of a worsening political situation, as it happens, for those from afar and on the ground.
Artificial intelligence and machine learning talent is in huge demand, with organisations such as Facebook and Google striving to employ data scientists for these emerging sectors. However, it’s evident that data scientists’ skills and expertise have applications far beyond the tech and business sectors. As data inevitably continues to increase in quality and volume, the value of data scientists is going to exceed expectations. There isn’t an industry which will not benefit from their insights, be they consumer or defence and security focussed. Make no mistake, data scientists have the potential to make a real difference.
Leo Borrett, Capability Adviser at DSTL (opens in new tab)
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