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Big Data and the Government
Introduction
In recent years, there has been an explosion of data generated by disparate sources, including social media, financial transactions, and sensor networks. This so-called Big Data has the potential to transform the way in which governmental agencies operate. For example, the Department of Homeland Security (DHS) has used Big Data to thwart terrorist attacks, by mining social media for suspicious activity. The Department of Health and Human Services has used Big Data to combat fraud in the Medicare system. And the Department of Education has used Big Data to improve student outcomes. With its ability to identify patterns and trends, Big Data has the potential to make government more efficient and effective. As the volume of data continues to grow, so too will the opportunities for government to harness its power. This paper will look at how Big Data can be used to improve DHS.
Background on the DHS
The Department of Homeland Security (DHS) is a federal government agency tasked with protecting the United States from terrorist attacks and other hazards. The agency was created in response to the 9/11 terrorist attacks, and it currently employs over 240,000 people. The DHS is responsible for a wide range of activities, including border security, counterterrorism, disaster response, and cyber security. The agency also administers the U.S. visa system and provides funding for state and local law enforcement agencies. In recent years, the DHS has come under criticism for its handling of immigration and border security issues. However, the agency remains an important part of the federal government's efforts to keep America safe (White, 2016).
Big Data
Big data is a term that describes the large volume of data that organizations and individuals create. But it is not just the size of data that is important. Big data can also refer to the variety and velocity of data. Variety refers to the different types of data that are being created, such as text, images, and videos. Velocity refers to the speed at which data is being generated, collected, and processed (Sagiroglu & Sinanc, 2013). Together, these two characteristics provide a wealth of information that can help organizations understand what is going on in the world (Kaisler et al., 2013). For example, by tracking the variety of data types relevant to an organization (e.g. targeted population demographics, purchasing history, website traffic, etc.), an organization can gain a better understanding of their target population and what kinds of issues or activities are most popular with the population. Additionally, by monitoring the velocity of data collection (e.g. how quickly customer needs change, how fast new products are adopted, etc.), they can anticipate population needs, desires, and demands and adjust policy accordingly. In this way, big data provides a valuable tool for organizations to make informed decisions about their operations.
The term "big data" is often used in reference to the technology and methods used to store, manage, and analyze large volumes of data. However, big data can also refer to the organizational opportunities that arise from working with large datasets. With the right tools and methods, organizations can use big data to gain insights into population behavior, improve operations, and make better decisions.
How Big Data Can Improve DHS
Big data has the potential to transform the way that the Department of Homeland Security (DHS) operates. By harnessing the power...…these concerns in mind, it is still clear that the use of Big Data can play an important role in the work of the DHS.
Conclusion
Big data has the potential to revolutionize the way that the Department of Homeland Security (DHS) functions. By definition, big data refers to extremely large data sets that may be too large or too complex for traditional data-processing techniques. However, with the right tools, this data can be analyzed to reveal valuable insights. For example, big data can be used to improve situational awareness by identifying patterns and trends that would otherwise be invisible. It can also be used to target resources more effectively, ensuring that limited resources are used as efficiently as possible. Big data can be used to analyze movements of money and people across borders to provide DHS with greater insight into potential criminal activities. It can be used to better understand social media activity so as to see how information and misinformation are being spread online and for what ends or purposes. By using Big Data, DHS could improve on a number of fronts, including crime prevention and the issue of pre-crime identification. In short, big data has the potential to transform DHS into a leaner, more effective organization. Given the importance of homeland security, this is an investment worth making. The main issue that DHS must be careful with is privacy, however. There is a fine line between gathering analyzing as much data as possible, and prying too much into the private lives of citizens. After all, it was Edward Snowden who blew the whistle on government spying years backso DHS has to be careful not to create another…
References
Aggarwal, A. K. (2019). Opportunities and challenges of big data in public sector. Webservices: Concepts, methodologies, tools, and applications, 1749-1761.
Coulthart, S., & Riccucci, R. (2022). Putting big data to work in government: the case ofthe United States border patrol. Public Administration Review, 82(2), 280-289.
Joh, E. E. (2014). Policing by numbers: big data and the Fourth Amendment. Wash. L.
Rev., 89, 35.
Kaisler, S., Armour, F., Espinosa, J. A., & Money, W. (2013, January). Big data: Issuesand challenges moving forward. In 2013 46th Hawaii international conference on system sciences (pp. 995-1004). IEEE.
Sagiroglu, S., & Sinanc, D. (2013, May). Big data: A review. In 2013 internationalconference on collaboration technologies and systems (CTS) (pp. 42-47). IEEE.
White, J. R. (2016). Terrorism and homeland security. Cengage Learning.
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