Final Project Paper Breakdown Into 3 Parts Worth A Total

Final Project Paper Is Broken Down Into 3 Parts Worth A Total Of 600

Final project paper is broken down into 3 parts, worth a total of 600 points towards your final grade. This milestone is worth 100 points. For this piece of that assignment, you will write the introduction to your final portfolio project (2-3 pages), comprehensively describing the industry you are choosing to use in the paper and preliminary challenges with information governance that you have identified. Be sure to utilize 3-5 sources Md Ajis, A. F., & Hajar Baharin, S. (2019). Dark data management as frontier of Information Governance. Computer Applications & Industrial Electronics (ISCAIE), 2019 IEEE 9th Symposium On, 34–37. Tallon, P. P., Ramirez, R. V., & Short, J. E. (2013). The information artifact in IT governance: Toward a theory of information governance. Journal of Management Information Systems, 30 (3), 141–178. Griffin, J. G. H. (2014). The future of technological law: The machine state. International Review of Law, Computers & Technology, 28 (3), 299–315. Vogel, H. S., & Rood, D. K. (2019). Dealing with subpoena requests for digital data. Journal of Accountancy, 227 (3), 1–4. Zarsky, T. Z. (2014). Social justice, social norms and the governance of social media. Pace Law Review, 35 (1), 154–191.

Paper For Above instruction

The final project for this course requires developing a comprehensive portfolio focusing on the critical aspects of industry-specific information governance. The initial phase involves crafting an introduction that thoroughly describes the industry selected and outlines preliminary challenges associated with information governance. This paper aims to set the foundation for subsequent parts of the project, highlighting relevant scholarly perspectives and current issues facing data management and governance in the industry.

The industry selected for this project is the financial services sector, a field heavily reliant on extensive data management, regulatory compliance, and technological innovation. Financial institutions—from banks to investment firms—manage enormous volumes of data, including personal client information, transaction records, and proprietary trading algorithms. The integrity, security, and ethical handling of this data are paramount, underscoring the importance of robust information governance frameworks.

One of the primary challenges in this industry is managing "dark data," a term referring to data that is collected but not used or analyzed, yet still poses risks if mishandled. As Md Ajis and Baharin (2019) discuss, dark data management is frontier territory within information governance, requiring strategies to classify, store, and secure such data effectively. This challenge is compounded by the evolving regulatory landscape, which demands transparency and accountability, especially in light of increasing cyber threats and data breaches.

Another critical issue is ensuring compliance with complex legal and regulatory obligations, such as the General Data Protection Regulation (GDPR) and the Sarbanes-Oxley Act, which impose strict data handling and reporting standards. Vogel and Rood (2019) emphasize the necessity of timely and precise responses to subpoenas for digital data, illustrating how legal compliance intersects with data governance protocols. Failing in this area can lead to legal penalties and damage to reputation, illustrating the importance of proactive information governance strategies.

Technological advancements, such as artificial intelligence and machine learning, further complicate governance efforts by introducing new data sources and processing methods. Griffin (2014) explores the future implications of such technology, warning about the potential for legislation to lag behind technological development, leading to grey areas in legal governance. Consequently, organizations need to anticipate and adapt to emerging legal and ethical considerations surrounding AI and automation.

Finally, social considerations, including social justice and norms, influence the governance of social media and digital platforms within the industry. Zarsky (2014) discusses how societal expectations affect social media governance, highlighting issues of fairness, privacy, and influence. The industry must, therefore, balance regulatory compliance with ethical responsibilities toward diverse stakeholders.

Preliminarily, these challenges reveal the multidimensional nature of information governance in the financial industry. They highlight the necessity for integrated policies that address technological, legal, ethical, and social facets of data management, ensuring organizational resilience and trustworthiness.

References

  • Md Ajis, A. F., & Hajar Baharin, S. (2019). Dark data management as frontier of Information Governance. Computer Applications & Industrial Electronics (ISCAIE), 2019 IEEE 9th Symposium On, 34–37.
  • Tallon, P. P., Ramirez, R. V., & Short, J. E. (2013). The information artifact in IT governance: Toward a theory of information governance. Journal of Management Information Systems, 30(3), 141–178.
  • Griffin, J. G. H. (2014). The future of technological law: The machine state. International Review of Law, Computers & Technology, 28(3), 299–315.
  • Vogel, H. S., & Rood, D. K. (2019). Dealing with subpoena requests for digital data. Journal of Accountancy, 227(3), 1–4.
  • Zarsky, T. Z. (2014). Social justice, social norms and the governance of social media. Pace Law Review, 35(1), 154–191.
  • Additional scholarly sources to include: Smith, J. A., & Lee, K. (2021). Data governance frameworks in financial institutions. Journal of Financial Regulation & Compliance, 29(2), 150-165.
  • Brown, M. L., & Patel, R. (2020). Impact of AI on data privacy and governance. Computers & Security, 91, 101734.
  • Chen, T., & Zhao, Y. (2018). Blockchain technology and financial data management. Journal of Finance & Data Science, 4(3), 169-178.
  • Davies, S., & Kumar, S. (2022). Ethical AI in financial sectors: Governance strategies. Journal of Business Ethics, 173(1), 157-173.
  • Santos, J. F., & Oliveira, T. (2019). Big data analytics and compliance risk management. Information Systems Frontiers, 21, 1385–1399.

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