There is currently a shortage of graduates with the necessary skills for jobs in data analytics and “Big Data”. Recently many new university degrees have been created to address the skills gap, but they are mostly computer science based with little coverage of statistics. In this chapter, the perceptions of graduates and academics about the types of expertise and the types of software skills required for this field are documented based on two online surveys in Australia and New Zealand. The results showed that Statistical Analysis and Statistical Software Skills were the most necessary type of expertise required. Graduates in industry identified SQL as the most necessary software skill while academics teaching in relevant disciplines identified R programming as the most necessary software skill for Big Data analysis. The authors recommend multidisciplinary degrees where the appropriate combination of skills in statistics and computing can be provided for future graduates.

Big Data / Data Science is a very important emerging area for statisticians. Software skills are increasingly important for statistical practitioners. Data science may be regarded by statisticians as a new name for statistical science but in industry and government the perception may be different. Recent advances in IT have enabled us to collect, store and easily access large amounts of data with modest cost. The capacity to analyse the data and use it for decision making has lagged behind. Software has been developed to filter, access and analyse data. Computer scientists and statisticians have been working separately, not jointly on this. This paper explores the implications of Big Data for statisticians’ education and aims to identify what skills are needed and software packages to use as well as the gaps between the perceptions of practitioners and academics about these issues.

There is currently a shortage of graduates with the necessary skills for jobs in data analytics and “Big Data”. Recently many new university degrees have been created to address the skills gap, but they are mostly computer science based with little coverage of statistics. In this chapter, the perceptions of graduates and academics about the types of expertise and the types of software skills required for this field are documented based on two online surveys in Australia and New Zealand. The results showed that Statistical Analysis and Statistical Software Skills were the most necessary type of expertise required. Graduates in industry identified SQL as the most necessary software skill while academics teaching in relevant disciplines identified R programming as the most necessary software skill for Big Data analysis. The authors recommend multidisciplinary degrees where the appropriate combination of skills in statistics and computing can be provided for future graduates.