Big Data, Data Science, Computer Science and Statistics Education

Recent advances in Information and Communication Technology (ICT), software and Artificial Intelligence (AI) have facilitated the collection, storage and easy access to vast amounts of data with low cost. The volume of such data exceeds society’s capacity to analyse, interpret and use it in decision making. Demand for people with the skills to extract information from the data is growing strongly. Some statisticians are of the view that Data Science is mostly hype and no more than a new name for statistical science. The perceptions of industry and government may be very different. The term “data scientist” appears frequently in recent job advertisements. For most statistical practitioners statistical and other software tools are essential for their work. Software has been developed to filter, access, visualise, and analyse data, handle large datasets, recognise patterns in it, even formulate hypotheses. Computer scientists and statisticians have been working independently of each other in this area. In this paper we examine what statistical skills and software tools are needed by graduates and the differences between the perceptions of practitioners and academics about these issues. The paper also investigates relevant degree programs in Australia regarding the coverage of statistics in data science degrees and of software skills in statistics degrees.