Visual OLAP : a New Paradigm for Exploring Multidimensional Aggregates

OLAP (On-Line Analytical Processing) technology provides interactive query-driven analysis of accumulated and consolidated business data for the purpose of decision making and knowledge extraction. Visualization is increasingly used as the means of gaining insight into huge data volumes of multidimensional data as the former exploits the profound ability of the human vision system to recognize patterns. This paper describes a new generation of analysis tools, characterized as Visual OLAP and based on the emerging visual exploration paradigm. In contrast to conventional tools that employ visualization primarily as user-friendly data presentation, visual OLAP turns visualization into the key method for both query specification and exploratory analysis. We propose a comprehensive visual exploration framework, which implements OLAP operations in form of powerful data navigation and allows users to explore data using a variety of interactive visualization techniques. A taxonomy of visual metaphors, from classical business charts to advanced 3D, multiscale, and hierarchical layouts accounts for different types of analytical tasks. A unified framework is obtained by abstracting various visualization options into a common presentation model and providing algorithms for mapping user interactions to database queries as well as mapping query results to a specified visual layout