Big Data as a buzz term has been with us for over a decade now, however in recent times it has possibly been surpassed by Artificial Intelligence (AI) as the pre-dominant tech buzz. But, if we take AI to be Machine Learning – which is the most commonly commercially available AI, then essentially this is the manipulation of all those vast data lakes (or oceans) that exist out there today – or in other words AI is an application group that is dependent upon Big Data.
The COVID-19 pandemic has only increased the volumes of this vast amount of data, and the need, use and specific demand for more innovative technical solutions in order to cope. Discussions around individual freedoms and data privacy have also been long debated – and with the advent of GDPR there is increased protection for us all, however the legislative infrastructure that provides cover for specific organisations to access more targeted data sets in order to keep us safe, must keep pace. The pandemic has highlighted specific limitations, but also potential approaches in how moving forward data can be collected, stored and analysed that ensures privacy but also provides enhanced opportunities.
Exponential data growth
The gathering of data from individuals, businesses and society as a whole continues to accelerate at such exponential rates as smart phones and their apps continue to collect ever more device and locational information – as shopping, mapping, social media, video and music streaming services become increaingly sophisticated; technology solutions such as the all-encompassing IoT arena are starting to get real world deployments beyond its own hype; and private enterprises deploy ever larger and sophisticated IT systems – see the explosion of Zoom and MS Teams over the past few months as a prime example in how organisations will look to position its enabling services. For those enterprises who have been caught short by the COVID-19 crisis, the investment in IT/IoT systems is only going to increase further – funding permitting – and become more focused on procuring the right solutions that blend human endeavour, appropriate tech and data accesses, to support mission delivery.
As the sources of data have been accelerating the proliferation of data – so have the tools that enable real world use of this data. On the one hand, connectivity increases apace, 5G and Fibre to the Premise (FTTP) telecoms operators can’t roll out their infrastructure fast enough, on the other, the applications that can manipulate the data – Artificial Intelligence/Machine Learning systems, Robotic Process Automation (RPA) and Data Analytic/Visualisation tools are maturing and there continues to be an increasing array of tools available for real world use cases.
Many organisations are now exploiting or at least recognising the value of tools and techniques to collect data – such as IoT technology that can monitor in real time, front office and back office employees temperatures un-intrusively whilst providing a state of the art radio communications – see Bodytrak, or the recent IBM RPA deployment at Avon and Somerset Police in the UK to help free up valuable human resource.
On top of this, the utilisation of tool sets that can tap into multiple data sources from structured to unstructured opensource data to support assessment and investigations, such as the solution from Siren to name but one of many, is supporting organisations to enhance their own capabilities and derive actionable insights. Rapid deployment models are now the norm for many of these tools – SaaS is a well established model, therefore the speed at which a new instance can be integrated into the relevant data sources and stood up is faster than ever before – which in turn brings and highlights commercial models that can and will help to drive down costs, and potentially free investment for additional opportunities.
However, organisations must work within the legislative frameworks that apply to them, which protects us and them.
Working within the legislative framework
There are constraints in how all data sources can be utilised though – the privacy concerns and individuals’ rights loom large for these organisations. Where legislation rightly constrains, it may be the case that adapting how particular problems are broken down and how the ask of service providers needs to change. Breaking down each problem, anonymising data and considering the specific questions to ask as well as building on crowd sourcing methods, would allow organisations to more effectively adapt their internal posture, exploit more market disruptors / thinkers / innovators to drive greater insights into behavioural patterns on any particular topic. Through this approach we can protect our individuals’ rights, whilst working within the current frameworks and ultimately protecting what it is they need to protect. Whilst this is a short introduction – we see that a slight change of focus, building on the numerous silo’d approaches adopted and utilising these together with enhanced working practices is what would be needed to ensure that law enforcement and national security agencies can take real advantage of the benefits that Big Data brings with it.
At Digilanti we have decades of experience in innovative technologies – such as in the Big Data arena and can help bring the benefits of these tools to law enforcement and national security organisations. Please get in touch to discuss how we could help you further.