Abstract
Advanced and predictive analytics are playing an increasingly important role in all industries. However, the productive use of new analytic methods and applications seems to stagnate. One reason for this is a lack of people with the necessary data science skills, especially for small and medium sized businesses. This paper proposes design principles that are important for enhancing the usage and adoption of applications for advanced and predictive analytics. The identified principles are implemented in a prototype application for predictive maintenance which can be used by employees without knowledge of data mining and machine learning.
Recommended Citation
Bourcevet,, Adrian; Piller, Gunther; Scholz, Matthias; and Wiesemann,, Jan, "Guided Machine Learning for Business Users" (2019). BLED 2019 Proceedings. 47.
https://aisel.aisnet.org/bled2019/47