Forgetting data intelligently in data warehouses

The amount of data stored in data warehouses grows very quickly so that they can get saturated. To overcome this problem, we propose a language for specifying forgetting functions on stored data. In order to preserve the possibility of performing interesting analyses of historical data, the specifications include the definition of some summaries of deleted data. These summaries are aggregates and samples of deleted data and will be kept in the data warehouse. Once forgetting functions have been specified, the data warehouse is automatically updated in order to follow the specifications. This paper presents both the language for specifications, the structure of the summaries and the algorithms to update the data warehouse.