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Comparison of Graduates' and Academics' Perceptions of the Skills Required for Big Data Analysis: Statistics Education in the Age of Big Data

Comparison of Graduates' and Academics' Perceptions of the Skills Required for Big Data Analysis: Statistics Education in the Age of Big Data
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Author(s): Busayasachee Puang-Ngern (Macquarie University, Australia), Ayse A. Bilgin (Macquarie University, Australia)and Timothy J. Kyng (Macquarie University, Australia)
Copyright: 2017
Pages: 27
Source title: Data Visualization and Statistical Literacy for Open and Big Data
Source Author(s)/Editor(s): Theodosia Prodromou (University of New England, Australia)
DOI: 10.4018/978-1-5225-2512-7.ch006

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Abstract

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.

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