Data intensive science is a major global growth area, as the volume, complexity and rate of digital data within governments and companies continues to rapidly increase. At the same time, powerful analysis techniques continue to evolve for obtaining radical insights into large datasets, including finding clusters and anomalies, as well as detecting and predicting dominant trends and correlations in such data. This data intensive science comes at a crucial time for global development. Major worldwide challenges, as encapsulated in the United Nations’ Sustainable Development Goals (SDGs), require multidisciplinary solutions, many of which include data science. Moreover, the South African National Development Plan (NDP) for 2030 recognises the need to “sharpen its innovative edge and continue contributing to global scientific and technological advancement” and “shift to a more knowledge-intensive economy”. Naledi Pandor – South African Minister of Science – stated in her 2016 budget speech; “A significant amount will be invested in big data, moving South Africa further on its path to becoming a knowledge economy. It is estimated that between 23,000 to 31,000 specialists with deep analytics and big data skills will be needed by 2018.” This is a highly ambitious goal for South Africa (SA), making the training of data scientists an urgent priority.