The Role of Big Data in National Security Decision Making

Governments and organizations have scaled up measures to increase the collection and utilization of data. In the advent of the Internet and use of gadgets, big data is 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 data into actionable insights whether that data is from within or outside of the boundaries. 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 explores the role of big data in the context of national security decision making.



Discussion



The article raises concern about the rare use of data analytics in the field of security studies. According to the author, data is the world's most valuable resource in the 21st century. 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). 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, instead of reactive to any prospect as well as boost productivity. So far, big data and information sharing have allowed easy coordination of activities between functions and key stakeholders in security (Crampton, 2015).



The article also raises concern on 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 complex dilemmas facing the security sector (Khan, 2014). 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 have deployed information delivery systems to individuals and functions across the borders. The aim of these systems in the current security environment is to provide information in real time to functions that impact 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 does not replace the need for human judgment (Khan, 2014). 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 data. The focus on tools can distract users from the insights (Mann, 2018). Today's 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 " Rosenthal, (2016) similar 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 factors 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 " Rosenthal, 2016).



The winners in this issue include the government, security institutions, citizens, enterprises and other stakeholders in the political sectors. These stakeholders have developed numerous approaches for the intelligent use of knowledge and information. With speedy development of communication and in the society, the growth in the accessibility, availability, and sharing of information and quality of the information among stakeholders improves decision-making (Hoffmann, 2017). Security is a public good. Availability of information and improved analysis would play a crucial role in organizing knowledge, to enable sharing, collaboration, categorizing, dissemination and storing of knowledge which can later be retrieved and accessible as meaningful across different contexts. The losers in this context are players that use data as leverage for activities such as terrorism and economic sabotage.



The issue is important as intelligence is extremely important to economies. We are in a technology-driven economy where 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). 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. The policies will 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.



Conclusion



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, by which insights are shaped, analyzed, shared and used.



References



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



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.



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



< https://theconversation.com/explainer-what-is-big-data-13780>

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