Data Product Model for boosting Agricultural Productivity in Sub-Saharan Africa

Abstract

Information systems have played vital roles in enhancing productivity in different domains using available data, especially in agriculture. With enormous data harvested from the direct farmers and remote sensor networks, there is still the gap of proper processing, and use to improve agricultural production in sub-Saharan Africa. As a means to an end, this work proposes a data product model that will boost agricultural production in sub-Saharan Africa. An object-oriented approach was employed to study the fundamental components of a data product and the processes involved. The study climaxed with the design of an implementable data product model using secondary data collected from secondary sources as input. The result was an interactive model that identified the actors, actions, sequence of data flow (Use Case and Sequence Diagram), and the model component. The proposed model has five distinct components: data production component; database component; Extract, Transform and Load component; the Data Team; and the Data Mart. The processes that go on within the components were itemized to be 7 processes.