Data Cleaning and Preparation in Non-Profit Organizations: Ensuring Accuracy, Consistency, and Usability
Author: Dr. Anna Neya Kazanskaia
Publisher: NEYA Global | NEYA Global Publishing
ORCID: https://orcid.org/0009-0009-5669-1676
DOI: https://doi.org/10.64357/neya-gjnps-dcp-2025
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About the Article
This article examines the essential processes of data cleaning and preparation in non-profit organizations, focusing on strategies to enhance accuracy, reliability, and usability. Internal records such as donor files, membership databases, and program data often contain errors, inconsistencies, or missing information. Techniques including duplicate removal, error correction, standardization, validation, and updating ensure that datasets reflect real-world conditions. Methods for addressing missing data—such as imputation, exclusion, and documentation—are discussed in relation to maintaining analytical validity. Data transformation techniques, including normalization, aggregation, encoding, binning, and pivoting, are presented as practical tools for preparing information for meaningful analysis. The article also highlights integration practices, such as merging datasets and warehousing, which expand analytical capacity while requiring careful validation. Practical recommendations include automating routine tasks, conducting periodic audits, and building staff capacity for long-term sustainability.
Key Topics
- Duplicate removal, error correction, and standardization
- Handling missing data through imputation, exclusion, and documentation
- Data transformation techniques: normalization, aggregation, encoding, binning, pivoting
- Integration and warehousing of multiple data sources
- Periodic audits and automated cleaning tools
- Ethical safeguards and governance in data management
- Capacity building for sustainable quality practices
Academic Value
The article contributes to the literature on non-profit management by situating data cleaning and preparation as strategic, rather than purely technical, processes. It connects operational practices with broader issues of accountability, transparency, and impact measurement. For academics, it reinforces the importance of methodological rigor in applied contexts. For practitioners, it offers practical, actionable steps to embed sustainable data management routines within organizations.
Suggested Citation
Kazanskaia, A. N. (2025). Data Cleaning and Preparation in Non-Profit Organizations: Ensuring Accuracy, Consistency, and Usability. NEYA Global Publishing. https://doi.org/10.64357/neya-gjnps-dcp-2025
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https://doi.org/10.64357/neya-gjnps-dcp-2025
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