A competency model for data scientists in Grain SA
| dc.contributor.advisor | Kotzé, M. | |
| dc.contributor.advisor | De Villiers, J. F. | |
| dc.contributor.author | Kruger, Yolandi | |
| dc.date.accessioned | 2016-12-13T11:42:48Z | |
| dc.date.available | 2016-12-13T11:42:48Z | |
| dc.date.issued | 2015-11 | |
| dc.description.abstract | With the current global population growth and the consequential increasing demand for food, agricultural productivity needs to increase. Grain SA is a leading role player in the agricultural industry and needs to serve the grain producers in South Africa effectively. Data science is a fairly new concept and is described as the management of large data sets from disparate sources to show results which assist in informed decision making. It is believed that the application of data science principles in agriculture may deliver many benefits, including increased productivity and profitability. Since data science is a new discipline that has not yet been implemented in Grain SA, it would need to be introduced to farmers and the agribusiness as a whole and the implementation thereof would need to be monitored. To capitalise on “big data”, Grain SA would be required to recruit and appoint a data scientist with the necessary skills and expertise to manage and distribute large data sets. The aim of this study is to conceptualise a competency model for data scientists in Grain SA. The adopted approach for the research was qualitative. Since the field of data science in agriculture is fairly new and information on the topic is very limited, the use of an exploratory study method was most suitable. The researcher conducted face-to-face interviews with 20 participants from nine organisations. The participants included individuals who are data scientists or work closely with data scientists. The interviews were conducted in the USA because the nation plays a leading role in agricultural innovation and offers a rich source of information for researchers in the field. The current role of data science in agriculture was explored by means of a literature review and an empirical study. The study describes the core competencies of a data scientist in agriculture and, based on this information, articulates the role of a data scientist in Grain SA. The core competencies of an effective data science coordinator in Grain SA are conceptualised and the development of the new competency model for data science coordinators in Grain SA is discussed in detail. | en_ZA |
| dc.identifier.uri | http://hdl.handle.net/11660/5243 | |
| dc.language.iso | en | en_ZA |
| dc.publisher | University of the Free State | en_ZA |
| dc.rights.holder | University of the Free State | en_ZA |
| dc.subject | Competencies | en_ZA |
| dc.subject | Competency model | en_ZA |
| dc.subject | Competency-based approach | en_ZA |
| dc.subject | Data science | en_ZA |
| dc.subject | Data scientist | en_ZA |
| dc.subject | Grain SA | en_ZA |
| dc.subject | Agriculture | en_ZA |
| dc.subject | Data science coordinator | en_ZA |
| dc.subject | Dissertation (MBA (Business Administration))--University of the Free State, 2015 | en_ZA |
| dc.title | A competency model for data scientists in Grain SA | en_ZA |
| dc.type | Dissertation | en_ZA |