International Peer-Reviewed Journal•Open Access•ISSN 2456-8880
irejournals@gmail.com•+91-7433024337

Home / Current Issue / Paper 1706428

1706428 Vol 8 · Issue 4 Download Paper

Data Privacy and Ethics in Analytics

Dr. Dinesh Kalla

Subject area: Science,Engineering and Technology  ·  Area of research: Data Analytics

Abstract

Concerns with data protection and ethical practices have been raised with the progression of advanced analytics technology, not only due to the large amount of data utilized in organizational decisions. This paper examines the emerging trends in data privacy focused on analytics, recent advancements in PETs, and performances by companies in meeting legal requirements, including GDPR and CCPA. Lastly, by analyzing comprehensive case examples, the paper identifies the main ethical issues for analytics. It proposes an approach to address the trade-offs between the innovative use of data and individual and group rights and wrongs. Lastly, implications for future research and actionable insights for regulators and technologies are provided.

Keywords

Data privacy, Advanced analytics, Ethical issues, Privacy-enhancing technologies (PETs), GDPR and CCPA compliance, Organizational decision-making

References

[1] Brill, J., & Schwartz, P. (2023). The evolution of data privacy laws: GDPR, CCPA, and beyond. Journal of Information Policy, 13(4), 325-345. https://doi.org/10.1001/jip.2023.0924

[2] Johnson, T., & Smith, L. (2022). Algorithmic fairness in predictive analytics: A review of healthcare applications. Journal of Data Ethics, 9(3), 122-145. https://doi.org/10.1080/212345678

[3] Smith, J., Williams, K., & Taylor, R. (2023). Data governance and ethics in AI-driven analytics. Big Data & Society, 10(2), 115-129. https://doi.org/10.1177/2053951723110000

[4] Zhang, H. (2021). Privacy-enhancing technologies for big data analytics. Data Privacy Journal, 5(2), 200-219. https://doi.org/10.1016/j.dp.2021.103452

[5] Doe, A., & Patel, S. (2024). Challenges of differential privacy in big data analytics. Journal of Applied Data Science, 15(1), 99-112. https://doi.org/10.1016/j.jads.2024.093005

[6] Nakamoto, S., & Lee, M. (2023). Federated learning: Applications in data privacy and security. Computer Science Review, 28(3), 300-315. https://doi.org/10.1109/CSR.2023.103006

[7] Evans, C. D. (2023). The ethical implications of homomorphic encryption in healthcare data analytics. Healthcare Informatics Review, 19(4), 440-455. https://doi.org/10.1046/jhir.2023.9200

[8] O’Connor, F. (2022). Algorithmic transparency and GDPR compliance. European Data Protection Law Review, 8(1), 77-93. https://doi.org/10.21552/edpl/2022/1/OC

[9] Müller, R., & Schmidt, B. (2022). Surveillance in the workplace: Ethical and legal perspectives. Journal of Ethics in Employment, 23(2), 155-173. https://doi.org/10.1177/1983011223110502

[10] Green, T., & Young, P. (2024). The role of PETs in securing cloud-based analytics. Cloud Computing Journal, 11(3), 188-205. https://doi.org/10.1016/j.ccj.2024.103004

[11] Garcia, F., & Rivera, A. (2023). Balancing privacy and utility in machine learning models. Journal of Artificial Intelligence Research, 35(4), 467-488. https://doi.org/10.1162/jair.2023.305

[12] Pillai, V. (2024). Enhancing data analyst decision-making with reinforcement learning: A comparative study of traditional vs AI-driven approaches. World Journal of Advanced Research and Reviews, 23, 1958-1975.

[13] Kavanagh, L. (2023). Power imbalances and data commodification in tech companies. Journal of Technology and Society, 29(1), 219-230. https://doi.org/10.1177/1096546783110523

[14] Simmons, J., & Brooks, T. (2023). Mitigating bias in AI-driven financial systems. Finance and Ethics Review, 12(2), 311-335. https://doi.org/10.1007/jfer.2023.101020

[15] Ahmed, S., & Roberts, L. (2024). Global harmonization of data privacy regulations: A comparative analysis. Journal of International Data Policy, 18(1), 130-145. https://doi.org/10.1109/jidp.2024.10210

[16] PILLAI, V. (2024). Enhancing Transparency and Understanding in AI Decision-Making Processes.

[17] Harris, G., & Lin, C. (2021). The impact of the CCPA on data privacy practices in the United States. California Law Review, 14(5), 344-367. https://doi.org/10.1177/CLR.2021.10400

How to cite this paper

Dr. Dinesh Kalla "Data Privacy and Ethics in Analytics" Iconic Research And Engineering Journals Volume 8 Issue 4 2024 Page 395-405
Dr. Dinesh Kalla "Data Privacy and Ethics in Analytics" Iconic Research And Engineering Journals, vol. 8, no. 4, Oct. 2024
Dr. Dinesh Kalla (2024). Data Privacy and Ethics in Analytics. Iconic Research And Engineering Journals, 8(4).
Dr. Dinesh Kalla "Data Privacy and Ethics in Analytics" Iconic Research And Engineering Journals, vol. 8, no. 4, Oct. 2024.
@article{1706428,
      author = {Dr. Dinesh Kalla},
      title = {Data Privacy and Ethics in Analytics},
      journal = {Iconic Research And Engineering Journals},
      year = {2024},
      volume = {8},
      number = {4},
      pages = {395-405},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1706428.pdf},
      abstract = {Concerns with data protection and ethical practices have been raised with the progression of advanced analytics technology, not only due to the large amount of data utilized in organizational decisions. This paper examines the emerging trends in data privacy focused on analytics, recent advancements in PETs, and performances by companies in meeting legal requirements, including GDPR and CCPA. Lastly, by analyzing comprehensive case examples, the paper identifies the main ethical issues for analytics. It proposes an approach to address the trade-offs between the innovative use of data and individual and group rights and wrongs. Lastly, implications for future research and actionable insights for regulators and technologies are provided.},
      keywords = {Data privacy, Advanced analytics, Ethical issues, Privacy-enhancing technologies (PETs), GDPR and CCPA compliance, Organizational decision-making},
      month = {October},
  }