Exploring OLAP Data with Parallel Dimension Views

Abstract

Existing OLAP user interfaces typically explore hierarchical multi-dimensional data through tabular data cube views. Aggregation is supported by dimension hierarchy level selection and filtering by slice and dice operations. Aggregation determines the size of data cube cells while filtering determines the cells in the view. Table based interfaces provide views that typically include two or three dimensions at a chosen level of aggregation. This paper describes an interface that is based on an alternative paradigm, parallel coordinates. However, instead of parallel axis, we use parallel dimension trees. The interface supports data aggregation and filtering operations. It supports both proportional and fixed value dimension scales. It supports a range of exploration tasks including viewing data distribution, comparing data distributions and viewing correlation. The main benefit of our interface is its support for rapid and flexible overviews across many dimensions and multiple hierarchy levels at the cost of less detailed views.