Browsing by Author "Haitamba, Pombili I.P."

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    A Centralised Hadoop-Based Framework for Big Data Analytics in Prime Ministerial Offices: A Namibian Case Study
    (Namibia University of Science and Technology, 2025-09-30) Haitamba, Pombili I.P.
    Big Data is reshaping the way governments operate, influencing how decisions are made and services delivered. However, most governments, particularly in developing countries, face challenges in managing the growing volume of data generated across public institutions. These challenges can be attributed to a lack of expertise in handling complex and diverse datasets generated in high volume which are becoming difficult for traditional databases to manage. In Namibia, the Office of the Prime Minister (OPM) plays a significant role in coordinating governance and public service administration. The OPM has a mandate to oversee Information and Communication Technology (ICT) in the Public Service and promote e-governance initiatives, which involve the usage and handling of data. However, despite its central role, data from different government ministries remains fragmented, building up silos. This fragmentation limits the government's ability to extract value from the data, hinders coordination across ministries, and ultimately leads to poor service delivery. This study addressed the challenges of data fragmentation within the OPM. It explored the feasibility of designing a centralised database system using Hadoop to integrate and analyse big data across ministries, with the goal of improved administrative efficiency, enhanced public service delivery, and promoting e-governance. Synthetic datasets were generated in Mockaroo, to represent datasets from government ministries. A Hadoop-based setup was undertaken to simulate a centralised database framework integrating all government ministries’ data in Hadoop Distributed File System (HDFS) for storage. A MapReduce job was run in Hadoop, using Java code for analyses across ministries, from Ministry of Home Affairs, Immigration, Safety and Security (MHAISS), Ministry of Labour (MoL), and Ministry of Education, Arts and Culture (MEAC). The job compared poverty indicators based on birth year, educational achievement, and employment status across the three ministries and aggregated the results for regional poverty analysis. The findings of this research show that Hadoop is a cost-effective, open-source framework that has the capabilities to store versatile datasets that currently exists within the Namibian public service into one centralised database that supports big data analysis. The processing layer of Hadoop, MapReduce was able to process a job in minutes that would normally take five to seven working days to complete in the OPMs current administration. Adopting this framework would enable the OPM to make informed decisions backed by evidence, eliminate inefficiencies in public service delivery, and enhance public trust through improved service delivery.