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Decision support for farmers in Africa: Analysis of the roles and competencies of data scientists in the grain industry

Martina Kotzé, Yolandi Kruger

Abstract


The use of data science as a decision-making tool in agriculture is becoming more evident. Data science principles and tools allow producers to access more consumable, accurate and timely information for making informed choices. Yet, the importance of farm data in effective decision making appears underrated in sub-Saharan Africa. To capitalise on ‘big data’, the sub-Saharan African grain industry needs competent data scientists to manage large data sets. To assist grain industry managers in selecting suitable candidates, an understanding of the data scientist’s role and required competencies is essential. This research identifies the core competencies and explores the role of data science in the grain industry. The results reveal the different types of data scientists and indicate that their role should not be narrowly delineated.



AJOL African Journals Online