A cost-effective, open-source architecture (Apache Spark) for big data analytics adoption in resource-constrained environments

Namibia’s economy depends heavily on Small and Medium Enterprises (SMEs), yet these businesses face an exceptionally high failure rate primarily due to poor strategic decision-making and a lack of market knowledge. While Big Data is globally recognized as a vital solution for gaining predictive customer insights, existing proprietary tools are often too expensive and technically complex for the resource-constrained Namibian SME sector. This research addresses the absence of an affordable, accessible, and contextually appropriate framework for analyzing customer data in these enterprises. By employing a mixed-methods approach, the study first identified that most local SMEs rely on fragmented, non-standardized tools like spreadsheets while facing critical shortages in software funding and skilled personnel. The primary outcome of this research is the SME Open-Source Big Data Adoption Framework, a multi-layered strategic model designed to guide small businesses through the complexities of data integration. The framework begins with Organizational Readiness, which emphasizes the foundational need for internal data governance, standardized collection processes, and improved data literacy among staff. This transitions into the Open-Source Implementation layer, which advocates for a "minimalist tool stack" utilizing cost-effective technologies like Apache Spark and Hadoop to remove the financial barriers associated with proprietary software. Finally, the framework addresses long-term viability through Support and Continuous Sustainability, proposing a Centralized Support Ecosystem potentially led by academic or government bodies to provide the technical mentorship and accountability required to mitigate the perceived risks of adopting non-commercial software in resource-constrained environments. Integrating the Technology Acceptance Model (TAM), Diffusion of Innovation (DOI), and Resource-Based View (RBV), the framework demonstrates that adopting low-cost open-source tools can unlock the perceived usefulness of data. Ultimately, this architecture provides a feasible route for SMEs to gain a competitive edge, improve strategic decisions, and drive sustainable growth within the Namibian landscape. Keywords: Namibian SMEs, Open-Source Big Data Tools, Customer Insights, Data Governance, Centralized Support Ecosystem.