For questions related to the data warehouse please contact Richard Dodds.
In 2011, Brandeis initiated the creation of a data warehouse (DW).
A data warehouse is a large database whose primary purpose is to support university decision-making through enhanced reporting and data integration. It typically performs these functions:
- For example, extracts data from an organization’s transactional systems (think SAGE, HR, PowerFAIDS, etc) on a regular basis (usually nightly)
- Validates the data to ensure that required information is present and accurate
- Loads the data into a centralized set of data marts (subsets of the larger warehouse that focus on specific functional areas)
- Links the information that comes in from the various transactional systems so that it can be analyzed to identify correlations, highlight trends, facilitate reporting, and support university decision-making.
The architecture of a data warehouse is structured differently than the transactional systems; it is designed to ease query writing and optimize reporting speed. Given the structure of the data and the large number of records involved, special reporting and analytical software is required to access the data. The products that fill this need fall under the umbrella term of Business Intelligence (BI). And since data warehouses and business intelligence products go hand-in-hand, the combination of the two is often shortened to the abbreviation DWBI.
Brandeis uses the EPM (Enterprise Performance Management) data warehouse that is delivered with its PeopleSoft software suite. The underlying database platform is Oracle, and the BI tool of choice is MicroStrategy. The data visualization tool of choice is Tableau.