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BI - Business Intelligence Glossary of Terms
Listing of terms and definitions used in BI.
Dashboard – A data visualization tool that displays the current status of metrics and key performance indicators for an enterprise. They consolidate and arrange numbers, metrics and sometimes performance scorecards on a single screen.
(Data) Mart – Logical divisions within the warehouse and are comprised of subject-specific dimensional data models designed around a specific institutional process. The warehouse includes Admissions and Recruiting Mart, Campus Community Mart, Student Records Mart and Student Financial Services Mart (includes some Financial Aid).
Dimension – A table in the star schema of the data warehouse that stores and categorizes data, such as people, items or other objects, in order to enable users to answer business questions.
ETL – Extract, Transform and Load. Extracts data from data source(s) and transforms the data for storing it in proper format or structure for querying and analysis purposes.
Fact – Tables that help quantify activities and typically consist of numerical values as it relates to the Dimensions.
MDW – Multidimensional Warehouse. After the ETL jobs move the source data into the OWS, another set of ETL jobs move the data into the MDW. Data is grouped as it is related to one or more business processes. Data is in a star schema format – a fact table surrounded by one or more dimension tables. The MDW contains data at the most granular level found in the source for flexible reporting.
OWS – Operational Warehouse Staging. The first step in preparing your data for multidimensional reporting is to load source data from your source transaction system into this layer. All table and field names and key structures are the same in the OWS as in the corresponding source table. In addition to the fields that match the source, there are fields that facilitate the incremental loading and source & error tracking.
Subject Area - Are physical tables that are grouped together in a dimensional model or star schema that reflect general data or functional categories. Subsequently, subject areas are synonymous with functional areas and each subject area identifies and groups the data that relates to a logical area of the business.