WLS Embedded LDAP Server
*By default, OBIEE 11g users and groups are now held in the WLS LDAP Server(C)
-More robust directory for storing user details
-Recommended for >1000 users
*WLS Admin Server Console now used for
creating and maintaining users(A)
*BI Server "outsources" all authentication,
authorization to FMW11g(not B)
*BI Administration tool now used for
subject area and row-level security,
connection pool passwords only(D)
WLS LDAP Server can be "swapped out" for alternative directories (MS AD etc)

Explanation
Oracle Business Intelligence Office Plug-In is a Windows application that is an optional feature under the Oracle Business Intelligence Presentation Services. The Plug-In provides a way to browse the Analytics catalog, select a report, and then drop that report into Microsoft Word or Excel.

Explanation
In OBIEE cache will be stored as files on the Hard Disk of the OBIEE Server in the form of files.

Dimensional Modeling - Slowly Changing Dimensions
*Type 1 - Overwrite Original Value A change does not require tracking
*Type 2 - Add a new record With Type II SCD, a new version of the dimension record (row) is created, and the existing version is marked as history. Each row does not correspond to a different instance of an entity but a different "state", a "snapshot" of the instance at a point in time.
Note: Tracking changes in dimension is referred in datawarehousing as slowly changing dimensions.
In the source system a lot of changes are daily made :
new customers are added,
addresses are modified,
new regional hierarchies are implemented,
or simply the product descriptions and packaging change.
These sorts of changes need to be reflected in the dimension tables and in several cases, the
history of the changes also needs to be tracked.
By remembering history, we are then able to look at historical data and compare it to their current
situation.

Explanation/Reference:
Note: A level-based measure is a column whose values are always calculated to a specific level of aggregation.
The calculation of this measure is independent of the query grain and used always the aggregation grain of the logical column.
Level-based measures allow :
* to return data at multiple levels of aggregation (the query grain and the level-based column grain) with one single query
* to create share measures (percentage), that are calculated by taking some measure and dividing it by a level-based measure. For example, you can divide salesperson revenue by regional revenue to calculate the share of the regional revenue each salesperson generates.