|
Term |
Definition |
|
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). |