The Role of Big Data in Decision Making in the Sphere of National Security

Governments and organizations have scaled up measures to increase the collection and utilization of data. After the introduction of the Internet and the increase in the use of gadgets, big data became one of the choices that decision-makers are embracing to leverage the broadening range of information assets for the benefit of economies. With the increasing array of data, there are key benefits attainable from turning more information, whether from within or outside of the boundaries, into actionable insights. The key benefits include improved decision making and new insights. In addition, data collected from monitoring activities can be used for planning and resource allocation purposes. While big data has significantly enhanced achievement of major objectives, it also raises concerns that did not exist previously. The article will explore the role of big data in the context of decision making in the sphere of national security.

The article raises concern about the rare use of data analytics in the field of security studies. The increased availability of data provides huge opportunities for data mining. However, governments and intelligence agencies have not fully taken advantage of the new capabilities (Khan 2014, n.p.). There are numerous information delivery solutions that allow governments and intelligence agencies to collect and utilize more information. The process enhances the ability to be proactive rather than reactive to any prospect as well as to boost productivity. So far, big data and information sharing have allowed easy coordination of activities between functions and key stakeholders in the sphere security (Crampton 2015, p.521).

 The article also raises concern on the extreme confidence in big data tools. Big data impacts intelligence collection, requirements, analysis, sharing, processing, exploitation, and security. As a result, technological solutions are viewed as the most effective means to resolve the complex dilemmas facing the security sector (Khan 2014, n..p.). The article recommends the implementation of analytics strategy that takes into consideration the importance of human element in the processes.

National security and intelligence institutions face intense pressure to afford information to users in a cost-effective way to assist in making critical decisions. To meet informational challenges, they the entities deployed information delivery systems to individuals and functions across the borders. The aim of such systems in the current security environment is to provide information in real time to functions that impact the key security processes. The increase in the utilization of big data analysis tools has created new concerns in the area of overdependence on the systems. The use of automated analysis would not replace the need for human judgment (Khan 2014, n.p.). The systems should be focused on information collection, processing, and delivery to ensure that the right information is accessed by users in near real-time or real-time

Big data is a significant issue, particularly in a period when there is growing enthusiasm for information. The focus on tools can distract users from the insights (Mann 2018, p.20). Modern information systems contain the largest, most sensitive and valuable data fundamental to the operations of economies. Hence, the nature of data collected increasingly becomes important due to its criticality to operations. According to Mian and Rosenthal (2016, n.p.) similarly to the traditional systems, the current systems have limitations that should be carefully considered by data users. The data revolution rhetoric considerably ignores political economy factors, such as actor incentives, historical aspects, and formal and informal setups. To make a difference, the revolution must acknowledge the real challenges and work within the constraints to improve data (Mian and Rosenthal 2016, n.p.).

The winners in this issue include the government, security institutions, citizens, enterprises, and other stakeholders in the political sector that have developed numerous approaches for the intelligent use of knowledge and information. The speedy development of communication and in the society, the growth in the accessibility, availability, sharing information, and improving its quality is beneficial for decision-making (Hoffmann 2017, p.3). Security is a public good. Availability of information and improved analysis would play a crucial role in accumulating and structuring knowledge, enabling its dissemination, cooperation, categorizing, and storing due to the possibility to access it across different contexts. The losers in this context are the players that use data as leverage for activities such as terrorism and economic sabotage.

The issue is of interest as intelligence is extremely important to economies. In the modern area of technology-driven economy, data is analyzed to yield actionable information essential to decision makers. It is considered that Intelligence has a potential positive impact through its ability to improve decision making at all levels of the economy (Khan 2014, n.p.).  An effective big data strategy that aligns with security and economic goals allows decision makers to make the best use of information.

There are no policies to resolve the issue. Governments and security institutions should develop policies to help in closing the existing gaps and reduce overreliance on systems by encouraging the use of human element in the processes. Additionally, governments and intelligence agencies will take full advantage of the new capabilities afforded by analytics.

Information advances and availability of huge chunks of data play vital roles in attaining security and economic goals. While available systems and solutions allow governments and institutions to generate and share more information for decision-making purposes, the value of big data lies in the process of easing the system that was shaped, analyzed, shared, and used.


Crampton, J.W., 2015. Collect it all: National security, big data and governance. GeoJournal, 80(4), pp.519-531.

Hoffmann, A.L., 2017. Making Data Valuable: Political, Economic, and Conceptual Bases of Big Data. Philosophy " Technology, pp.1-4.

Mann, L., 2018. Left to other peoples’ devices? A political economy perspective on the big data revolution in development. Development and Change, 49(1), pp.3-36.

Mian, A. and Rosenthal, H., 2016. Introduction: Big Data in Political Economy.


Khan, A., 2014. Explainer: what is big data? Accessed 30 March 2018,

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