The methodology is based on a conceptual representation of the Enterprise, which is exploited both in the integration phase of the Warehouse information sources and during the knowledge discovery activity on the information stored in the Warehouse.
Publicly available data, e.g., by the Federal Statistical Office, other public or scientific institutions or historic and current intra-corporate data (e.g., in a data warehouse) are viable sources.
Normally, this is associated with the data coming to the data warehouse form multiple source systems [28].
The multiple tiers allow implementers and designers to decouple the enterprise data warehouse from both sourcing and acquisition functions and information delivery and data provisioning functions.
When the data warehouse is the source of data for all data marts, the result is integrity of data in the data marts.
The experiment in building a multiple representation data warehouse from eight data sources in the context of the GEMURE (Generalization and Multiple Representations for on-demand map production and delivery) project is also discussed.
Finally, warehouse databases integrate data sources in one place: examples of this approach include BioWarehouse (13), Biozon (14), Atlas (15), EnsMart (16) and IGD (17).
This paper describes Dr. Warehouse®, an open source data warehouse oriented toward clinical narrative reports and designed to support clinicians' day-to-day use.
In this paper, we propose a methodology for designing data warehousing applications from various sources.
GreenPlum is an open source data warehouse, licensed under Apache Inc., which offers fast analytics on petabyte-scale data with efficient query processing via parallel processing and optimization.
Many IT practitioners and researchers advocate that data models of data warehouses should incorporate the sources of their data in order to achieve maximum efficiency.
