Big Data Governance Framework for Ethio Telecom

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Addis Ababa University


With the digitization of most operations, the popularization of various social media channels, blogs, deployment of various types of devices, sensors, hand-held smart devices, wearables, and the explosion in Internet usage, large volumes of data are being generated on a regular basis. Today, businesses are searching for ways to successfully manage and optimize these large datasets due to a massive amount of information being swapped every day and the growing need to make better data-driven decisions. Big data refers to huge data sets with large, more varied, heterogeneous, and complex structures that are expensive to retrieve, examine, and visualize using conventional data processing technologies. One of the most pressing issues in dealing with big data is the adoption of suitable big data governance frameworks to customize big data in a sufficient manner to enable quality data access for effective knowledge extraction using machine learning techniques. It also aspires to outline the blueprint that governs the storage and processing of data from owners and consumers in a truthful manner within the applicable regulatory landscape. Ethio telecom is one of the major big data custodians in Ethiopia that lacks such insight. The main objective of this work, therefore, is to explore and propose a big data governance framework for Ethio telecom based on governance activities related to data handling in Ethio telecom networks. The proposed framework consists of three domains and within the domains, there are nineteen components identified to formulate the structure. Towards that end, the research adopted Design Science Research as a research approach coupled with a mixed methodology for data collection and analysis. Towards achieving the objective, a review of literature on big data, big data analytics, big data management, big data governance, and previously designed big data governance frameworks were explored with the aim to develop a suitable framework and identify common characteristics and shortcomings in the available big data governance frameworks. Primary data were obtained through survey questionnaires and key informant interviews to maintain organizational context and domain-specific big data governance specifications. As governed by the chosen research strategy, these two contributions (qualitative and quantitative data) are integrated to design a detailed big data governance framework suitable for the Ethio telecom setting. Expert validation was then used to assess the proposed big data governance framework. As a result, the research process and study results are thought to be acceptable, indicating the usability and applicability of the proposed framework.



Big Data, Big Data Analytics, Big Data Governance, Big Data Governance Framework