Data and Reporting Services - Glossary

This glossary contains some terms and definitions used in BrioQuery and in the Data Warehouse Explorer section of our web pages.

• Business Area: Data Warehouse Explorer term which groups information in the Warehouse according to data type. e.g. Financial, General, Student, Human Resources.

• Data Item: Component of a table catalog, also called a field.

• Description: Data Warehouse Explorer term: a lengthier explanation of the table or the field in a table. The table and field description contains information about the data in the table and field respectively.

• Limits: Criteria used to narrow the scope of a query.

• Master Data: Information describing characteristics of information such as cost collectors, customers, or vendors.

• Metadata: Data (information) about data. Term which describes the data.

• Outliner: A BrioQuery tool used to construct and modify reports, Pivot reports and Charts.

• Pivot Report: A report that you can construct in BrioQuery to display data from the Results section of the query. This kind of report allows you to aggregate data according to dimensions that you choose and also interchange the dimensions to re-orient the view of the data by using the Pivot feature.

• Primary Provider: This is the MIT organization or computer system which supplies the data to the Warehouse.

• Process: A BrioQuery command that executes a query to retrieve data from the Data Warehouse which is downloaded to your computer and displayed in the Results section as well as reports, Pivot reports and Charts that have been set up and stored as part of the file.

• Query: A set of criteria that is used to retrieve data from the Data Warehouse. Queries are made up of data items (also called fields) to be retrieved and can also have limits set on the scope of the data and/or sorting order specified.

• Report: A report that you can construct in BrioQuery to display data from the Results section of the query. In the Report section there are a variety of options for arranging the data and formatting it. You can arrange data in tables by categories and create "Smart" reports by embedding pivots and charts in them.

• Results: The data that has been retrieved after processing a query and displayed in the Result section of BrioQuery. If the query was constructed incorrectly or values used for limits were either incorrect or not authorized for your use, no data is displayed.

• Sensitivity: Data Warehouse Explorer term indicating how sensitive the data is. There are four levels of sensitivity of data at MIT:
  • Public: This data is not sensitive at all, and can be freely shared with anyone.
  • MIT Only: This data can be used only within the MIT community. This data must not be shared beyond the MIT community.
  • Sensitive: This data is sensitive, and should only be used by individuals who need it to perform their job. Special access controls should be in place for this type of data.
  • Extremely Sensitive: This data is of the highest sensitivity. EXTREME caution should be used whenever dealing with this type of data. Paper documents with this data on it should be shredded. This classification is reserved for relatively few types of data.

• Star/table Group: The tables in the Data Warehouse are designed to be grouped together in certain ways - these groupings are referred to as Stars because diagrams of these groupings resemble star patterns.

• Table Catalog: A list of tables displayed in BrioQuery which you are authorized to use to build queries.

• Table Name: This is the name of a table stored in the Data Warehouse. These table names are the same as those seen in the "Table Catalog" in BrioQuery.

• Tables: A table (also called topics) is a logical groupings of data items (also called fields) that represent a facet of the Data Warehouse.

• Type: The table types "Fact" and "Dimension" refer to how tables are used in constructing queries. A Fact table is typically the center of a subject area and contains values which are to be measured by a query (e.g. Purchase Order Dollar Amount, Financial Transaction Actual Amount, Count of Students, Test Score). Information which is to be summed and totaled on a report usually resides in the central Fact table.
  A Dimension table typically contains master data (such as GL Accounts, Cost Collectors, Academic Terms, Department Names). Dimension tables are used to provide different groupings or categorizations on a report and to limit queries by choosing only the desired sets of data (e.g. choosing a particular fiscal period or small set of account numbers).