Parallel coordinates for visualizing multi-dimensional geometry
CG International '87 on Computer graphics 1987
An overview of data warehousing and OLAP technology
ACM SIGMOD Record
OLAP solutions: building multidimensional information systems
OLAP solutions: building multidimensional information systems
Visualizing multi-dimensional data
ACM SIGGRAPH Computer Graphics
Polaris: A System for Query, Analysis, and Visualization of Multidimensional Relational Databases
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
Advanced visualization for OLAP
DOLAP '03 Proceedings of the 6th ACM international workshop on Data warehousing and OLAP
Exploring OLAP aggregates with hierarchical visualization techniques
Proceedings of the 2007 ACM symposium on Applied computing
Unraveling multi-dimensional data using pDView
Proceedings of the 14th International Conference on Extending Database Technology
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Business data collection is growing exponentially in recent years. A variety of industries and businesses have adopted new technologies of data storages such as data warehouses. On Line Analytical Processing (OLAP) has become an important tool for executives, managers, and analysts to explore, analyze, and extract interesting patterns from enormous amount of data stored in data warehouses and multidimensional databases. However, it is difficult for human analysts to interpret and extract meaningful information from large amount of data if the data is presented in textual form as relational tables. Visualization and interactive tools employ graphical display formats that help analysts to understand and extract useful information fast from huge data sets. This paper presents a new visual interactive exploration technique for an analysis of multidimensional databases. Users can gain both overviews and refine views on any particular region of interest of data cubes through the combination of interactive tools and navigational functions such as drilling down, rolling up, and slicing. Our technique allows users who are not experts in OLAP technology to explore and analyze OLAP data cubes and data warehouses without generating sophisticated queries. Furthermore, the visualization in our technique displays the exploration path enhancing the user's understanding of the exploration.