Recommendation functionality for smart data analytics toolbox to support choosing task-relevant data analytics tools

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Though many enhancements are still possible and needed, data analytics software packages invaded all segments of industrial businesses. Since product designers are not specialized data analysts, an op- portunity of enhancement is to provide advice by smart data analytics toolboxes (SDATBs). For in- stance, SDATBs can provide guidance at selecting commercially available data analytics tools (DATs) for a specific design-related task. The reported work focused on the implementation of a recommendation functionality for selecting DATs for different appli- cations. The paper presents the proposed solution, which (i) interprets the designer’s input, (ii) pro- poses a description of the problem identified by the designer, (iii) reasons with the warehoused DATs and (iv) recommends DATs matching the designer’s task at hand. Besides presenting the needed func- tionality, the rules used for selecting DATs are dis- cussed and the computational algorithms are speci- fied. A computational feasibility testing of the tool recommendation functionality has been done considering the application case of enhancing a wash- ing machine by white goods designers. The testing process showed that the realized functionality works correctly from a computational point of view and that it achieves sufficiently good tool matching. It compensates for the knowledge lack of product de- signers concerning selection of data analytics tools and reduces time and effort for tools selection. The outcomes of this study will be used in a follow up research to develop a SDATB providing even more comprehensive support for product designers.