Using Data Analysis Tools in Non-Profit Organizations: From Spreadsheets to Advanced Analytics

This article explores the spectrum of data analysis tools available to non-profit organizations, from accessible spreadsheet platforms to advanced statistical and programming environments. Microsoft Excel, LibreOffice Calc, and Google Sheets provide essential functions such as formulas, pivot tables, and real-time collaboration, while advanced tools such as SPSS, R, and Python enable large-scale statistical modeling, automation, and integration with databases. Practical considerations—including budget, staff skill levels, data complexity, and system compatibility—shape organizational tool selection. By demonstrating spreadsheet formulas like SUM, AVERAGE, IF, and VLOOKUP alongside advanced applications in R and Python, the article highlights how organizations can strategically adopt tools that align with their missions. Ultimately, building competence in both basic and advanced tools empowers non-profits to transition from descriptive reporting to predictive and evaluative analytics, strengthening decision-making, accountability, and social impact.

Authors

Publication Details

Published
2025-01-01
DOI
https://doi.org/10.64357/neya-gjnps-udat-2025
Citations
1
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
2.28
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article

Using Data Analysis Tools in Non-Profit Organizations: From Spreadsheets to Advanced Analytics

Anna Neya Kazanskaia
1 citations
Big Data and Business Intelligence
2.28
article

Using Data Analysis Tools in Non-Profit Organizations: From Spreadsheets to Advanced Analytics

Anna Neya Kazanskaia
article en
1 citations

Abstract

This article explores the spectrum of data analysis tools available to non-profit organizations, from accessible spreadsheet platforms to advanced statistical and programming environments. Microsoft Excel, LibreOffice Calc, and Google Sheets provide essential functions such as formulas, pivot tables, and real-time collaboration, while advanced tools such as SPSS, R, and Python enable large-scale statistical modeling, automation, and integration with databases. Practical considerations—including budget, staff skill levels, data complexity, and system compatibility—shape organizational tool selection. By demonstrating spreadsheet formulas like SUM, AVERAGE, IF, and VLOOKUP alongside advanced applications in R and Python, the article highlights how organizations can strategically adopt tools that align with their missions. Ultimately, building competence in both basic and advanced tools empowers non-profits to transition from descriptive reporting to predictive and evaluative analytics, strengthening decision-making, accountability, and social impact.

Openalex Percentile: Top 9%
Big Data and Business Intelligence
2.28
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