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Business & Information Systems Engineering

Document Type

Research Paper

Abstract

Generating insights and value from data hasbecome an important asset for organizations. At the sametime, the need for experts in analytics is increasing and thenumber of analytics applications is growing. Recently, a newtrend has emerged, i.e. analytics-as-a-service platforms, thatmakes it easier to apply analytics both for novice and expertusers.Inthisstudy,theauthorsapproachthesenew servicesbyconducting a full-factorial experiment where both inexperi-enced and experienced users take on an analytics task with ananalytics-as-a-service technology. The research proves thatalthough experts in analytics still significantly outperformnovices, these web-based platforms do offer an advantage toinexperienced users. Furthermore, the authors find that ana-lytics-as-a-service does not offer the same benefits acrossdifferent analytics tasks. That is, they observe better perfor-mance for supervised analytics tasks. Moreover, this studyindicates that there are significant differences between novi-ces. The most important distinction lies in the approach theytake on the task. Novices who follow a more complex,although structured, workflow behave more similarly toexperts and, thus, also perform better. The findings can aidmanagers in their hiring and training strategy with regards toboth business users and data scientists. Moreover, it can guidemanagers in the development of an enterprise-wide analyticsculture. Finally, the results can inform vendors about thedesign and development of these platforms.

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