From Spreadsheets to Scalability

Databases as a Next Step for Non-Profits

Authors

  • Sidney J. Shapiro Dhillon School of Business, University of Lethbridge, Lethbridge, Alberta
  • Vivian Oystrick Cambrian College, Greater Sudbury, Ontario
  • Alison (Xiang) Liu University of Lethbridge, Lethbridge, Alberta
  • Naveen Kumar Vadlamudi University of Lethbridge, Lethbridge, Alberta

DOI:

https://doi.org/10.3138/cjpe-2023-0050

Keywords:

data analysis, data management, data mining, database systems, database training, IT infrastructure, organizational capacity, non-profit organizations, program evaluation

Abstract

This article discusses the evolution of data management strategies for non-profit organizations, transitioning from spreadsheets to more scalable database systems. As non-profits grow and their data becomes more complex, the need for robust database solutions becomes apparent. The article examines the types of databases suitable for program evaluation, highlighting the benefits and limitations of each. It also explores the challenges non-profits face in implementing these systems, such as infrastructure limitations, lack of full-time IT support, and the need for staff training. Through case studies, successful database implementations are analyzed to derive best practices. The findings emphasize the importance of tailored database solutions, ongoing staff training, and collaborations with IT experts for non-profits to maximize the benefits of database systems in their program evaluations.

References

Ahrens, J. D., & Sankar, C. S. (1993). Tailoring database training for end users. MIS Quarterly, 419–439.

Azcorra, A. (2021). Lightning guide to databases with Microsoft Access and SQL: A practical guide to database design with Microsoft Access and SQL.

Bach-Mortensen, A. M., & Montgomery, P. (2018). What are the barriers and facilitators for third sector organisations (non-profits) to evaluate their services? A systematic review. Systematic Reviews, 7(1), 13.

Beynon-Davies, P. (2004). Microsoft Access. In Database systems (pp. 446–456). Springer.

Blumberg, R., & Atre, S. (2003). The problem with unstructured data. Dm Review, 13(42–49), 62.

Broman, K. W., & Woo, K. H. (2018). Data organization in spreadsheets. American Statistician, 72(1), 2–10.

Cutler, J., & Dickenson, M. (2020). Databases. In Computational frameworks for political and social research with Python (pp. 99–116).

Deka, G. C. (2014). A survey of cloud database systems. IT Professional, 16(2), 50–57.

Engø-Monsen, K. (2020). Big data for social good. In The Oxford handbook of mobile communication and society (p. 292).

Fasano, R., & Shapiro, J. J. (1991). Computerizing the small non-profit: Computer consultants’ perspective. Computers in Human Services, 8(1), 129–145.

Finkler, S. A., Calabrese, T. D., & Smith, D. L. (2022). Financial management for public, health, and not-for-profit organizations. CQ Press.

Gonzales, A. L., & Yan, H. Y. (2020). Non-profit reuse as a solution to reducing digital divides and technology maintenance inequalities. In Organizing inclusion (pp. 73–89). Routledge.

González Berrios, G. (2022). Data culture in non-profit organizations (NPOs). Polytechnic University of Puerto Rico. http://hdl.handle.net/20.500.12475/1859

Hassan, M. A. (2021). Relational and NoSQL databases: The appropriate database model choice.

Kamal, M. (2024, March 15–16). Understanding ICT adoption and impact in nonprofits using the capabilities framework – multi case analysis. Proceedings of the Southern Association for Information Systems Conference. Gulf Shores, AL.

Leckel, A., Veilleux, S., & Dana, L. P. (2020). Local open innovation: A means for public policy to increase collaboration for innovation in SMEs. Technological Forecasting and Social Change, 153, 119891.

McCosker, A., Yao, X., Albury, K., Maddox, A., Farmer, J., & Stoyanovich, J. (2022). Developing data capability with non-profit organisations using participatory methods. Big Data & Society, 9(1), 20539517221099882.

Meier, A., & Kaufmann, M. (2019). NoSQL databases. In Meier and Kaufmann, SQL & NoSQL databases: Models, languages, consistency options and architectures for big data management (pp. 201–218). Springer Vieweg Wiesbaden.

Naeem, M., Jamal, T., Diaz-Martinez, J., Butt, S. A., Montesano, N., Tariq, M. I., De-la-Hoz-Franco, E., & De-La-Hoz-Valdiris, E. (2022). Trends and future perspective challenges in big data. In Pan, J.S., Balas, V.E., Chen, C.M. (Eds.), Advances in Intelligent Data Analysis and Applications. Smart Innovation, Systems and Technologies 253 (pp. 309–25). Springer, Singapore.

Ortega-Rodríguez, C., Licerán-Gutiérrez, A., & Moreno-Albarracín, A. L. (2020). Transparency as a key element in accountability in non-profit organizations: A systematic literature review. Sustainability, 12(14), 5834.

Ranjan, J., & Foropon, C. (2021). Big data analytics in building the competitive intelligence of organizations. International Journal of Information Management, 56, 102231.

Rathi, D., & Given, L. M. (2017). Non-profit organizations’ use of tools and technologies for knowledge management: A comparative study. Journal of Knowledge Management, 21(4), 718–740.

Rey-Garcia, M., Liket, K., Alvarez-Gonzalez, L. I., & Maas, K. (2017). Back to basics. Nonprofit Management and Leadership, 27(4), 493–511.

Scquizzato, S. (2024). Data integration and data-driven evaluation for the non-profit sector. A study case: Response innovation lab [Master’s thesis]. Università Ca’ Foscari Venezia. http://hdl.handle.net/10579/26275

Shapiro, S. J., & Oystrick, V. (2018). Three steps toward sustainability: Spreadsheets as a data-analysis system for non-profit organizations. Canadian Journal of Program Evaluation, 33(2), Article 2.

Soelton, M., Noermijati, N., Rohman, F., & Mugiono, M. (2021). Improving the performance non-profit organizations? Academy of Strategic Management Journal, 20(5), 1–13.

Strekalova, Y. A., & Bouakkaz, M. (2022). Semi-structured data. In Encyclopedia of big data (pp. 816–819). Springer.

Tony-Okeme, A. F. (2021). Microsoft Office application competencies possessed by office technology and management students for employability and self-reliance [Doctoral dissertation, Kwara State University]. ProQuest Dissertations & Theses.

Zanti, S., Berkowitz, E., Katz, M., Nelson, A. H., Burnett, T., Culhane, D., & Zhou, Y. (2022). Leveraging integrated data for program evaluation: Recommendations from the field. Evaluation and Program Planning, 95, 102093.

Cover of The Canadian Journal of Program Evaluation / La Revue canadienne d’évaluation de programme. Pale blue background with bilingual English–French title at the top. Central box lists Volume 39, Number 2, December 2024 and article titles and authors under section headings. Website and ISSN appear at the top; University of Toronto Press logo at bottom right.

Downloads

Published

2025-01-29

How to Cite

Shapiro, S. J., Oystrick, V., Liu, A. (Xiang), & Vadlamudi, N. K. (2025). From Spreadsheets to Scalability: Databases as a Next Step for Non-Profits. Canadian Journal of Program Evaluation, 39(2), 363–372. https://doi.org/10.3138/cjpe-2023-0050

Issue

Vol. 39 No. 2 (2024): December

Section

Research and Practice Notes

License

Copyright (c) 2025 Sidney J. Shapiro, Vivian Oystrick, Alison (Xiang) Liu, Naveen Kumar Vadlamudi

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Authors contributing to The Canadian Journal of Program Evaluation agree to release their articles under the Creative Commons Attribution-Noncommercial 4.0 (CC-BY-NC) license. This licence allows this work to be copied, distributed, remixed, transformed, and built upon for any purpose provided that appropriate attribution is given, a link is provided to the license, and changes made were indicated.

Authors retain copyright of their work and grant the journal right of first publication.

Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.