Our research examines data-driven visualization methods for archival purposes. Using data extracted from a large and heterogeneous digital collection, we created an information visualization that uses RDBMS and treemap to enable archival analysis. Different views present the collection's structure and properties at different levels of aggregation and abstraction, transforming 1,000,000 data points into information that enables observation and decision-making.