Evaluation of Business-Driven Reference Architecture for Big Data Analytics Implementation by Public Sector Organizations in Resource-Constrained Setting: A Case Study of Uganda

Big Data Analytics (BDA) is a new area at the nexus of agenda, public sector organizations, and government business. It may satisfy the growing need for trustworthy, cost-effective services in the public sector for better, more informed decision-making processes. BDA has been proposed on the planning schedules of several public sector organizations and the government. Therefore, from the previous work, using Uganda as a case study, specifically the Uganda Bureau of Statistics (UBOS), Ministry of Health (MoH), and Ministry of Education and Sports (MoES), this study aims to evaluate a designed Business-Driven Reference Architecture for Big Data Analytics Implementation (BRABDAI) in public sector organizations. Using a quantitative research method, the BRABDAI was analytically assessed using a structured walkthrough technique by 18 IT experts in the fields of data analysis, IT/IS management, and solution architecting. The assessment criterion was composed of three components: functionality, usability/applicability, and traceability. The Statistical Package for the Social Sciences (SPSS) software was used for data analysis. The findings showed that the BRABDAI was useful for resolving the key issues preventing the successful implementation of the BDA in public sector organization settings and that it was also understandable and traceable. To improve the usage and acceptability of BDA implementation in public sector organizations, the study advises more research on this topic.

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Publication Details

Journal
Tanzania Journal of Engineering and Technology
Published
2024-08-31
DOI
https://doi.org/10.52339/tjet.v43i2.930
Primary Topic
Big Data and Business Intelligence
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article
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article

Evaluation of Business-Driven Reference Architecture for Big Data Analytics Implementation by Public Sector Organizations in Resource-Constrained Setting: A Case Study of Uganda

Noe Elisa, Frederick Chali, Matendo Didas
Tanzania Journal of Engineering and Technology
Big Data and Business Intelligence
article

Evaluation of Business-Driven Reference Architecture for Big Data Analytics Implementation by Public Sector Organizations in Resource-Constrained Setting: A Case Study of Uganda

Noe Elisa, Frederick Chali, Matendo Didas
article en

Abstract

Big Data Analytics (BDA) is a new area at the nexus of agenda, public sector organizations, and government business. It may satisfy the growing need for trustworthy, cost-effective services in the public sector for better, more informed decision-making processes. BDA has been proposed on the planning schedules of several public sector organizations and the government. Therefore, from the previous work, using Uganda as a case study, specifically the Uganda Bureau of Statistics (UBOS), Ministry of Health (MoH), and Ministry of Education and Sports (MoES), this study aims to evaluate a designed Business-Driven Reference Architecture for Big Data Analytics Implementation (BRABDAI) in public sector organizations. Using a quantitative research method, the BRABDAI was analytically assessed using a structured walkthrough technique by 18 IT experts in the fields of data analysis, IT/IS management, and solution architecting. The assessment criterion was composed of three components: functionality, usability/applicability, and traceability. The Statistical Package for the Social Sciences (SPSS) software was used for data analysis. The findings showed that the BRABDAI was useful for resolving the key issues preventing the successful implementation of the BDA in public sector organization settings and that it was also understandable and traceable. To improve the usage and acceptability of BDA implementation in public sector organizations, the study advises more research on this topic.

Tanzania Journal of Engineering and TechnologyVol. 43(2)
The University of Dodoma (TZ)
Peace, Justice and strong institutions
Openalex Percentile: Top 69%
Big Data and Business Intelligence
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