A competency model for data scientists in Grain SA
Loading...
Files
Date
2015-11
Authors
Kruger, Yolandi
Journal Title
Journal ISSN
Volume Title
Publisher
University of the Free State
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.
Description
Keywords
Competencies, Competency model, Competency-based approach, Data science, Data scientist, Grain SA, Agriculture, Data science coordinator, Dissertation (MBA (Business Administration))--University of the Free State, 2015