Final Project Report: Use of Big Data Technology in Government

This final project report investigates the application of big data technology within the government sector, examining its potential benefits and associated challenges. The research explores how big data can enhance efficiency, improve healthcare, and strengthen national security. It also addresses the improvement of education and decision-making processes. The report highlights key findings, including the importance of requirement gathering, risk assessment, and the use of a conceptual framework for project development. The project identifies potential risks, particularly technical risks, related to big data implementation. The report also includes a comprehensive bibliography of relevant research. The report concludes that big data can significantly improve government operations and citizen services, provided that challenges are addressed effectively.

Final Project Report
(Use of Big Data Technology in Government)

Introduction
 The use of big data technology has been described through put the
research.
 The research has covered the benefits and the challenges of the big
data in the government sector.

Possible Advantages
 Increase of efficiency in the functioning of the government.
 Improvement of the health care sector maintained by the
government.
 Improvement of the education sector with the help of the big data
technology.
 Improving the national security using the big data technology.
 Improvement of the decision making process through the use of big
data.

Possible Challenges
 Problem regarding the implementation of this emerging technology.
 Less people is aware about the application of big data.
 The business perspective of big data is neglected.

Lesson Learned
 Certain steps those are needed to be followed during the course of
the compilation of the project.
 Gathering of the requirements is important as it will help to mitigate
the scope creep in the development of the project.

Cont..
 There is a need for the proper assessment of the risks.
 Proper assessment of the risks will help to mitigate the impact from
the changed situation on the project.

Result and Findings
 It has been seen that the application of the big data can be done
through the conceptual framework in the development of the project.
 Apart from that the field those will be benefitted in the government
sector after the implementation of the big data tools can be done
through this emerging technology.

Cont..
 From the research it has been found out that the use of the big data
big data helps the government in the decision making process
regarding national security and the education system.
 Apart from that it has been found out the analysis of the external
data sources will help the government organization to find out the
flaws in the national security.

Cont..
 The improvement of the government health care sector can be done
through the using of the big data analysis.
 The data can be collected from the citizen regarding the required
steps for the development of the health care system.

Cont..
 Apart from that the use of the big data technology can be used for
diminishing the unemployment.
 The use of big data technology in the organization will be helpful to
understand the needs for the human resource on the basis of the
proficiency rate.

Risks Associated
 Some of the risks associated with this application.
 From the findings and results it has been seen that the main problem
regarding the implementation of the big data in the government
sector is the technical risk.

Conclusion
 . In order to do the project in a proper way, there are certain steps
those are needed to be followed.
 The paper has discussed the importance of maintaining the
requirement analysis

Bibliography
 Anthopoulos, L. G., & Reddick, C. G. (2016). Understanding electronic government research and smart city: A framework and empirical
evidence. Information Polity, 21(1), 99-117.
 Anthopoulos, L., Reddick, C. G., Giannakidou, I., & Mavridis, N. (2016). Why e-government projects fail? An analysis of the Healthcare. gov
website. Government Information Quarterly, 33(1), 161-173.
 Charalabidis, Y., Alexopoulos, C., & Loukis, E. (2016). A taxonomy of open government data research areas and topics. Journal of Organizational Computing
and Electronic Commerce, 26(1-2), 41-63.
 Cordella, A., & Tempini, N. (2015). E-government and organizational change: Reappraising the role of ICT and bureaucracy in public service
delivery. Government Information Quarterly, 32(3), 279-286.
 Glaeser, E. L., Kominers, S. D., Luca, M., & Naik, N. (2018). Big data and big cities: The promises and limitations of improved measures of urban
life. Economic Inquiry, 56(1), 114-137.
 Harsh, A., & Ichalkaranje, N. (2015). Transforming e-government to smart government: A South Australian perspective. In Intelligent Computing,
Communication and Devices (pp. 9-16). Springer, New Delhi.
 Hashem, I. A. T., Chang, V., Anuar, N. B., Adewole, K., Yaqoob, I., Gani, A., ... & Chiroma, H. (2016). The role of big data in smart city. International Journal of
Information Management, 36(5), 748-758.
 Höchtl, J., Parycek, P., & Schöllhammer, R. (2016). Big data in the policy cycle: Policy decision making in the digital era. Journal of Organizational Computing
and Electronic Commerce, 26(1-2), 147-169.
 Janssen, M., van der Voort, H., & Wahyudi, A. (2017). Factors influencing big data decision-making quality. Journal of Business Research, 70, 338-345.
 Kruse, C. S., Goswamy, R., Raval, Y. J., & Marawi, S. (2016). Challenges and opportunities of big data in health care: a systematic review. JMIR medical
informatics, 4(4), e38.
 Saraladevi, B., Pazhaniraja, N., Paul, P. V., Basha, M. S., & Dhavachelvan, P. (2015). Big Data and Hadoop-A study in security perspective. Procedia computer
science, 50, 596-601.
 Wamba, S. F., Akter, S., Edwards, A., Chopin, G., & Gnanzou, D. (2015). How ‘big data’can make big impact: Findings from a systematic review and a
longitudinal case study. International Journal of Production Economics, 165, 234-246.
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