\n\nSupervisor: Emiel Caron\n\n<\/p>\n\n\n\n
The central question of this research is: ‘how can business dashboards be extended with explanatory analytics capabilities to support business analysts in answering managerial questions?<\/em> \u2019. The relevance for answering this question for business comes from the lack of explanatory functions in current business intelligence tools, and more specifically in business dashboards. This is a problem for business analysts that must browse large amounts of data visually to discover interesting patterns. Furthermore, visual analysis is not only slow and expensive, but also highly subjective through the bias of the analyst (Fayyad, Piatetsky-Shapiro, & Smyth, 1996). Lastly, explanatory functions can help the effort to move to a more data-driven decision-making process. Tools that can assist in the effort of making these tasks easier and quicker are valuable.<\/p>\n\n\n\n The objective of this design-oriented research is to develop applications that can extend current dashboard solutions like MS PowerBI with functions to 1) find exceptional values in the dashboard and 2) give explanations why the exceptions have occurred. <\/p>\n\n\n\n