The authors briefly introduce the various types of metadata used in data warehousing. This includes naming conventions, source system definitions, hard and soft rules, metadata for staging areas, cross-reference tables, and access control lists. They explain the attributes recommended (for tracking) in projects, and the components in the architecture used to store the metadata. In addition, the chapter covers how to implement the error mart, used to capture erroneous data from ETL and other processes. The chapter is complemented with hands-on examples for the Meta Mart, the metrics vault (and metrics mart) and the error mart.