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Challenges of Identifying and Utilizing Big Data Analytics in a Resource-Constrained Environment: In the Case of Ethiopia

机译:在资源受限的环境中识别和利用大数据分析的挑战:以埃塞俄比亚为例

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Big data analytics (BDA) is the process of capturing and storing huge volume of data which has different formats and generated in high Velocity. It also refers to the process of analyzing big data for the purpose of decision making, strategic planning and policy formulation. Some of the applications of BDA include market segmentation, sales forecasting, weather forecasting, payment fraud detection, crop diseases detection, e-commerce analysis and users purchasing recommendation and others. The application of BDA is not only left for economically developed regions. It is also important for resource-constrained environments. In this study, challenges of identifying and utilizing big data analytics in the resource-constrained environment in the case of Ethiopia have been explored using some case. The case studies considered potential industries that can generate big data in Ethiopia. Ethiopian Telecommunication Corporation, Agricultural Transformation Agency, Payment systems like Hello Cash and Ethiopian Educational Networks (EthERNet) were considered as a case study. In the study, a qualitative grounded approach has been applied. Data was collected using a semi-structured interview approach. As data analysis result and discussion indicated that even if the selected potential industries have been generated big data they are not using it fully for the purpose of decision making. Potential challenges were identified in the identifying and utilizing of BDA in a resource-constrained environment. Some of these areas: lack of BDA awareness, data integration challenge, lack of skilled experts in the area, lack of data correctness and completeness, lack of standardized data registry, lack of leadership and management skill, issue of data privacy and infrastructure challenges including a huge volume of storage device constraint. Based on the identified challenges of BDA implementations in this study and possible application areas of BDA in those industries, a conceptual framework of the study were formulated.
机译:大数据分析(BDA)是捕获和存储海量数据的过程,这些数据具有不同的格式并以高速度生成。它还指为决策,战略计划和政策制定目的而分析大数据的过程。 BDA的一些应用包括市场细分,销售预测,天气预报,付款欺诈检测,作物病害检测,电子商务分析以及用户购买推荐等。 BDA的应用不仅留给经济发达的地区。这对于资源受限的环境也很重要。在这项研究中,对于使用埃塞俄比亚的案例,探索了在资源受限的环境中识别和利用大数据分析的挑战。案例研究考虑了可以在埃塞俄比亚产生大数据的潜在行业。埃塞俄比亚电信公司,农业转型局,Hello Cash等付款系统和埃塞俄比亚教育网络(EthERNet)被视为案例研究。在研究中,采用了定性的定性方法。使用半结构化访谈方法收集数据。数据分析结果和讨论表明,即使选定的潜在行业已经产生了大数据,他们也没有将其完全用于决策目的。在资源受限的环境中,在识别和利用BDA方面发现了潜在的挑战。其中一些领域:缺乏BDA意识,数据集成挑战,该领域缺乏熟练的专家,数据缺乏正确性和完整性,缺乏标准化的数据注册表,缺乏领导和管理技能,数据隐私问题和基础架构挑战,包括大量的存储设备约束。基于本研究中已确定的BDA实施挑战以及BDA在这些行业中可能的应用领域,制定了研究的概念框架。

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