
In this work, we discuss how analytics is evolving in industry and academia. To assess industry needs, we conducted a text-mining study of online job postings for analytics-related positions. We also conducted a survey of academic programs in analytics-related master’s programs to ascertain topic coverage relative to industry needs. Based on these two studies, we discuss gaps that we believe need to be addressed. While industry moves along the analytics maturity spectrum from descriptive to predictive to prescriptive optimization-based analytics, analytics master’s programs are focusing less on optimization and more heavily on predictive analytics, thus creating the future potential for a gap in the analytics training provided by academia and the future analytics needs of industry.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 19 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
