Ethical Considerations in Advanced Data Analytics for Non-Profit Organizations
Author: Dr. Anna Neya Kazanskaia
Publisher: NEYA Global Publishing
Article | NEYA Global Journal of Non-Profit Studies
Year: 2025
ORCID: https://orcid.org/0009-0009-5669-1676
DOI: https://doi.org/10.64357/neya-gjnps-adv-dt-an-10
This material forms part of the NEYA Global knowledge architecture. Institutional, organizational, professional, training, consulting, curriculum, program design, or implementation use requires an active license from NEYA Global
Explore Architecture →
Module Overview →
Request Institutional Access →
About the Article
Ethical considerations are fundamental in the deployment of advanced data analytics within non-profit organizations, where sensitive information about donors, beneficiaries, and volunteers is regularly handled. This article explores the principles of privacy, security, fairness, and transparency, emphasizing robust safeguards, responsible practices, and compliance with frameworks such as GDPR and CCPA. Case studies illustrate best practices, including anonymizing beneficiary datasets, monitoring AI-driven donor targeting, and maintaining compliance documentation. Adoption strategies include data minimization, encryption, access controls, fairness audits, and continuous staff training. By embedding ethical standards into data-driven initiatives, non-profits can strengthen trust, protect stakeholders, and ensure that analytics advance mission-driven goals responsibly.
Key Topics
- Data ethics in non-profit organizations
- Privacy, security, and anonymization practices
- Ethical AI, fairness audits, and accountability
- Governance and compliance with GDPR and CCPA
- Data minimization and responsible data use
- Building organizational cultures of ethical practice
Suggested Citation
Kazanskaia, A. N. (2025). Ethical Considerations in Advanced Data Analytics for Non-Profit Organizations. NEYA Global Journal of Non-Profit Studies. Neya Global Publishing. https://doi.org/10.64357/neya-gjnps-adv-dt-an-10
References
| Floridi, L., & Taddeo, M. (2016). What is data ethics? Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 374(2083), 20160360. https://doi.org/10.1098/rsta.2016.0360 | ||||
| Brynjolfsson, E., & McElheran, K. (2016). The rapid adoption of data-driven decision-making. American Economic Review, 106(5), 133-139. https://doi.org/10.1257/aer.p20161016 | ||||
| Kazanskaia, A. N. (2025). Advanced Data Analytics Techniques for Social Impact. NEYA Global Publishing. https://doi.org/10.64357/advanced-data-analytics-social-impact-2025 | ||||
| Kazanskaia, A. N. (2025). Data Analysis: Turning Information into Insight. NEYA Global Publishing. https://doi.org/10.64357/data-analysis-insight-2025 | ||||
| Kazanskaia, A. N. (2025). Program Evaluation: Frameworks and Best Practices. NEYA Global Publishing. | ||||
| Kazanskaia, A. N. (2025). Visualizing Impact: Data Communication Strategies. NEYA Global Publishing. | ||||
| Kazanskaia, A. N. (2025). Ethical Considerations in Data Analysis for Non-Profit Organizations. NEYA Global Journal of Non-Profit Studies. | ||||
| Kazanskaia, A. N. (2025). Building a Data-Driven Culture in Non-Profit Organizations: Leadership, Literacy, and Organizational Transformation. NEYA Global Journal of Non-Profit Studies. https://doi.org/10.64357/neya-gjnps-adv-dt-an-11 | ||||
| Provost, F., & Fawcett, T. (2013). Data science for business: What you need to know about data mining and data-analytic thinking. O'Reilly Media. | ||||
| Salamon, L. M. (2014). The resilient sector revisited: The new challenge to nonprofit America. Brookings Institution Press. https://doi.org/10.5040/9780815750949 | ||||
| Chambers, R. (2014). Rural development: Putting the last first. Routledge. https://doi.org/10.4324/9781315835815 | ||||
