Automated analytics: the organizational impact of analytics-as-a-service

author: Tine Van Calster, KU Leuven
published: Oct. 25, 2016,   recorded: August 2016,   views: 932

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Nowadays, many web-based applications are emerging that offer an easy-to-use platform for data analytics to the masses, which usually has fast processing times and large data storage capabilities. These tools fall under the term of 'analytics-as-a-service' (AaaS) and offer an alternative for expensive, in-house analytics infrastructures. Moreover, they might also prove to be interesting in situations where expertise in analytics is not readily available. Through an experimental study, this paper investigates which inexperienced users achieve the best analytical results when using this type of self-service analytics technology. These characteristics range from individual features to the user task approach and the type of task that the novice has to undertake. Furthermore, we also compare the quantitative performance of these inexperienced users to the scores of analytics experts who use the same tool. Our findings indicate that although an expert in analytics still outperforms a novice, we can list some recommendations for selecting the best candidate for performing an analytics task with AaaS, even though he/she does not necessarily have a lot of experience in the field.

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