A data warehouse stores integrated information from multiple distributed data sources. In effect, the warehouse stores materialized views over the source data. The problem of ensuring data consistency at the warehouse can be divided into two components: ensuring that each view reflects a consistent state of the base data, and ensuring that multiple views are mutually consistent. In this paper we study the latter problem, that of guaranteeing multiple view consistency (MVC). We identify and define formally three layers of consistency for materialized views in a distributed environment. We present a scalable architecture for consistently handling multiple views in a data warehouse, which we have implemented in the WHIPS(WareHousing Information Project at Stanford) prototype. Finally, we develop simple, scalable, algorithms for achieving MVC at a warehouse.
Yue Zhuge, Hector Garcia-Molina, Janet L. Wiener