Comparison of graduates' and academics' perceptions of the skills required for big data analysis: statistics education in the age of big data

Busayasachee Puang-Ngern*, Ayse A. Bilgin, Timothy J. Kyng

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

3 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationData Visualization and Statistical Literacy for Open and Big Data
EditorsTheodosia Prodromou
Place of PublicationHershey, PA
PublisherIGI Global
Chapter6
Pages126-150
Number of pages25
ISBN (Electronic)9781522525134
ISBN (Print)9781522525127
DOIs
Publication statusPublished - 20 Mar 2017

Publication series

NameAdvances in Data Mining and Database Management (ADMDM)
PublisherIGI Global
ISSN (Print)2327-1981
ISSN (Electronic)2327-199X

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