From data capture to data visualization, the process of data transformation is a search for meaning through dozens to hundreds to millions of units of information. This course is both a conceptual and practical introduction to contemporary datascape, big and small. Through projects, code tutorials and critical readings, we approach data as a tool for research and design, as a basis for interactive digital projects, and as a form of knowledge that deeply impacts our culture and society. We cover the practical process of data transformation from data structures and architecture; to mining and aggregation; to visualization. Students will work with publicly available datasets, design their own databases, and learn how to critically read graphical representations of knowledge. Projects will provide the opportunity for students to build and design data visualizations, develop back-end code for interactive prototypes, and acquire the basic skills of data query and management. Through readings and presentations we will examine ethical, historical and humanistic approaches to data design and theory. Computational methods covered by this class will include APIs, text and image libraries, quantitative methods, mapping and GeoCoding. Students will be introduced to programming languages for data management (JavaScript and SQL) and for visualization (Processing/PSjs). Prior programming experience may be advantageous, but is not necessary.