Another critical application technology for GW will be the data warehouse, and in some specific cases the data mart. The benefit of a Data Warehouse is that data are cleaned, properly defined, and have only one official interpretation, one value, and are organized and indexed for meaningful business data retrieval. It is not an easy transition to clean and reorganize data into a warehouse, but the benefits are enormous once done. Data may be queried regardless of the origination source. Historical and time sequenced data are also available for trending analysis and other what-if questions.
Correct metadata is the key to a good data warehouse implementation.
This is extremely important when data from two different systems are being merged into a common data warehouse. Significant data analysis and administration will be required to define and build the appropriate GW metadata, but once this is done, there will be a plethora of very powerful data management and reporting tools available for the end-user to deploy for fast reporting and analysis. Banner data is already in hierarchical format within an Oracle database, while the existing finance data within MSA is in a much older flat file VSAM environment. While the New Finance team is currently working to totally redefine the financial piece of the GW data model, sufficient Banner data already exists to create an immediate data reference foundation for such a warehouse, if desired. The diagram below illustrates the process of creating a warehouse from today's disparate on-line systems.