Authors: Bernd Neumayr, Konrad Linner, Michael Schrefl
Tags: 2011, conceptual modeling
Business analysts frequently use Cockpits or Dashboards as front ends to data warehouses for inspecting and comparing multi-dimensional data at various levels of detail. These tools, however, perform badly in supporting a business analyst in his or her business intelligence task of understanding and evaluating a business within its environmental context through comparative data analysis. With important business knowledge either unrepresented or represented in a form not processable by automatic reasoning, the analyst is limited in the analyses that can be formulated and she or he heavily suffers from information overload with the need to re-judge similar situations again and again, and to re-discriminate between already explained and novel relationships between data. In an ongoing research project we try to overcome these limitations by applying and extending semantic technologies, such as ontologies and business rules, for comparative data analysis. The resulting Semantic Cockpit assists and guides the business analyst due to reasoning about various kinds of knowledge, explicitly represented by machine-processable ontologies, such as organisation-internal knowledge, organisation external domain knowledge, the semantics of measures and scores, knowledge about insights gained from previous analysis, and knowledge about how to act upon unusually low or high comparison scores. This paper outlines the architecture of the Semantic Cockpit and introduces its core ideas by a sample use case.Read the full paper here: https://link.springer.com/chapter/10.1007/978-3-642-24574-9_9
