Modelling Multidimensional Data in a Dataflow-Based Visual Data Analysis Environment
Multidimensional data analysis is currently being discussed in terms like OLAP, data warehousing, or decision support, mainly concentrating on business applications. Numerous OLAP-tools providing flexible query facilities for datacubes are being designed and distributed. Typical analysis sessions with these kind of systems comprise long and branching sequences of exploratory analysis steps which base upon each other. While concentrating on single functions and processing steps, management of this analysis process as a whole is scarcely supported.
This paper proposes a dataflow-based visual programming environment for multidimensional data analysis (VIOLA) as an approach to deal with this problem. Providing a foundation of basic operations, data processing, navigation, and user interaction, an appropriate data model (MADEIRA) is developed. Epidemiological studies, i. e. investigations of aggregate data on populations, their state of health, and potential risk factors, will serve as a leading example of a typical application area.
KeywordsAggregation Function Category Attribute Multidimensional Data Graph Node Analysis Session
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