2019/08/21 by Alessandra Maciel Paz Milani, Fernando V. Paulovich, Milani, Alessandra +4
Business, Management and Accounting · Computer Science · #Big Data and Business Intelligence #Data Analysis with R #Data Visualization and Analytics #FOS: Computer and information sciences #H.2 #Human-Computer Interaction (cs.HC) #I.3
paper · pdf · doi:10.48550/arxiv.1908.07894
openalex publication_date 2019/08/21 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The current information age has increasingly required organizations to become\ndata-driven. However, analyzing and managing raw data is still a challenging\npart of the data mining process. Even though we can find interview studies\nproposing design implications or recommendations for future visualization\nsolutions in the data mining scope, they cover the entire workflow and do not\nfully focus on the challenges during the preprocessing phase and on how\nvisualization can support it. Moreover, they do not organize a final list of\ninsights consolidating the findings of other related studies. Hence, to better\nunderstand the current practice of enterprise professionals in data mining\nworkflows, in particular during the preprocessing phase, and how visualization\nsupports this process, we conducted semi-structured interviews with thirteen\ndata analysts. The discussion about the challenges and opportunities based on\nthe responses of the interviewees resulted in a list of ten insights. This list\nwas compared with the closest related works, improving the reliability of our\nfindings and providing background, as a consolidated set of requirements, for\nfuture visualization research papers applied to visual data exploration in data\nmining. Furthermore, we provide greater details on the profile of the data\nanalysts, the main challenges they face, and the opportunities that arise while\nthey are engaged in data mining projects in diverse organizational areas.\n