An overview of data warehousing and OLAP technology
ACM SIGMOD Record
Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Totals
Data Mining and Knowledge Discovery
IEEE Transactions on Visualization and Computer Graphics
Query, analysis, and visualization of hierarchically structured data using Polaris
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
A visual interface technique for exploring OLAP data with coordinated dimension hierarchies
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
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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.