A data warehouse is the concept of data extracted from operational systems and made available as historical snapshots for ad-hoc queries and scheduled reporting. Characteristics that distinguish data in the data warehouse from data found in the operational environment are that it is: organized in such as way that relevant data is clustered together for easy access, several copies of the data from various points in time are kept together, and once the data is placed into the data warehouse it is not updated. Rather, the historical snapshots stored in the Data Warehouse are periodically refreshed with data from the operational databases.
The main problem addressed by a data warehouse is that end-users have a difficult time producing ad-hoc or other specialized queries and reports. This is due to several factors:
- Most of the data is stored in ADABAS, which is difficult for end-users to access.
- The data stores were designed for transaction processing not ad-hoc reporting.
- Obtaining the data or a report usually requires waiting for a programmer to either develop the report or provide a customized download program.
- All of the data may not be consistent as of the same point in time.
- There may not be enough copies of the data kept for historical reporting in the operational systems.
- End-users do not have the knowledge of what is kept in the existing data stores.
The data warehouse addresses these factors and provides many advantages to the end-users of the University including:
- Improved end-user access to a wide variety of University data
- Increased data consistency
- Additional documentation of the data
- Potentially lower computing costs and increased productivity
- Providing a place to combine related data from separate sources
- Creation of a computing infrastructure that can support changes in computer systems and business structures
- Empowering end-users to perform any level of ad-hoc queries or reports without impacting the performance of the operational systems