While the first two books in the Making Sense of Data series discussed data visualization, the central role that graphics could play in data exploration and mining was not addressed. If graphics are to take center stage in the exploration and understanding of a dataset, careful consideration needs to be given to typical tasks performed by professionals and analysts including how they share and discuss what has been learned about their data with others, the design of an interaction model to effectively support these tasks, and the implications of that interaction model for system and component architectures as well as data models. Building an interactive business intelligence system that supports incremental visual exploration and data mining requires knowledge that crosses many disciplines including statistics, data mining, statistical and data mining graphics, human-computer interaction, and computer science. This book integrates relevant information spread across research papers and books from these disciplines and describes how to build systems that combine mainstream software technologies with advanced approaches in data visualization such as graphical grammars. The book is divided into four parts. Part I - Exploring data through graphics introduces readers to data exploration through graphics and describes the history of exploratory data analysis and data mining, how analysts interact with systems to perform common tasks, and how exploration could be done utilizing graphical grammars to support a style of interaction that makes graphics the central tool for exploration. Part II - Design discusses the interaction, user interface and usability design principles criteria that should be considered alongside business issues, and the implications that the interaction design decisions have on system design. Part III - Architecture covers software design decisions from the high level system architecture to the details of the component architecture. Part IV - Application covers data exploration in business and includes case studies showing how the graphical exploration process could be used to explore data in chemical genomics and other application areas.