This paper describes the meta-data warehouse ofCredit Suisse that is productive since 2009. Like most otherlarge organizations, Credit Suisse has a complex applicationlandscape and several data warehouses in order to meet theinformation needs of its users. The problem addressed by themeta-data warehouse is to increase the agility and flexibility ofthe organization with regards to changes such as the developmentof a new business process, a new business analytics report, or theimplementation of a new regulatory requirement. The meta-datawarehouse supports these changes by providing services to searchfor information items in the data warehouses and to extract thelineage of information items. One difficulty in the design of sucha meta-data warehouse is that there is no standard or well-knownmeta-data model that can be used to support such search services.Instead, the meta-data structures need to be flexible themselvesand evolve with the changing IT landscape. This paper describesthe current data structures and implementation of the CreditSuisse meta-data warehouse and shows how its services helpto increase the flexibility of the whole organization. A seriesof example meta-data structures, use cases, and screenshots aregiven in order to illustrate the concepts used and the lessonslearned based on feedback of real business and IT users withinCredit Suisse.