Building on Statistics Canada’s metadata-driven architectural principle and metadata strategy themes: drive, make available, structure and manage, Picasso is an enterprise solution for statistical data and metadata management. Automated business rules will ensure metadata is gathered uniformly, adhering to common architecture, governance and policy instruments. Picasso, a three-year project launched in 2015, replaces local solutions with a hub for managing metadata for all surveys, administrative files and record linkage projects; a data service centre function for all ‘fit for use’ data files; and enterprise search and discovery using metadata to facilitate reuse of information. New tools and components include a metadata designer with an entity lifecycle management and registration process. The solution architecture is based on a hybrid relational/semantic graph (RDF) core registry and repository with a data model driven by standard vocabularies, e.g. SKOS/XKOS, PROV-O, and reference models, e.g. GSIM, DDI 4 and SDMX. Picasso component and external systems interact with the RDF core via a Data Access Layer and Entity Services to access metadata entities via Common Information Exchange Models. Standard vocabularies and models ensure efficient information exchange internally and to external users through the Agency’s website and Research Data Centres.