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This research work is an assessment of how data analytics contributes to environmental sustainability. The objectives of the study were: To determine how data analytics affects environmental sustainability, To find out barriers to data analytics and environmental sustainability, To discover opportunities for data analytics and environmental sustainability, and To ascertain how data analytics aligns with environmental conservation goals and values. This research adopts a quantitative questionnaire approach as the method of data collection. Questionnaires were administered to 50 persons; the study used descriptive and inferential statistics to analyse the data gathered, and regression analysis was used to generate inferences from the data, using Statistical Packages for Social Sciences (SPSS). The regression model shows that there is an overall statistical significance between the independent variables (effect of data analytics, barriers of data analytics, and opportunities of data analytics) and the dependent variable (environmental sustainability with a corresponding p-value of 0.038). Therefore, the study recommends that organisations and governments invest in robust data analytics infrastructure to effectively collect, process and analyse environmental data. Efforts should be made to address the barriers identified in the analysis, such as implementation challenges, data quality issues, and scalability concerns, and enhancing data literacy and building analytical skills among environmental professionals is crucial for maximising the potential of data analytics.
Divyeshkumar Vaghani (Tue,) studied this question.