Creating Logical Time Dimensions Compared to modeling an ordinary dimension, the time dimension requires just two additional steps: selecting the Time option in the Logical Dimension dialog, and designating a chronological key for every level of every dimension hierarchy.
Note: Time dimensions and chronological keys. You can identify a dimension as a time dimension. At least one level of a time dimension must have a chronological key. The following is a list of some guidelines you should use when setting up and using time dimensions:
*At least one level of a time dimension must have a chronological key.
*All time series measures using the AGO, TODATE, and PERIODROLLING functions must be on time levels. AGO, TODATE, and PERIODROLLING aggregates are created as derived logical columns.
Reference: Oracle Fusion Middleware Metadata Repository Builder's Guide for Oracle Business Intelligence Enterprise Edition. Working with Logical Dimensions

You have three sort of fragmentation:
Fact-based / Dimension-based fragmentation
Content-based / Value-based fragmentation
Level-based fragmentation / aggregate navigation
You can combine the techniques above to construct powerful design that are known as Complex partitioning / fragmentation. When you fragment a dimension, you are automatically in a complex fragmentation.

A: OBIEE 11g is centred on WebLogic Server as the underlying application server architecture.
B: If you want to scale out this infrastructure, you would typically run the OBIEE 11g installer on a second server, and instead of choosing to do a new install, you'd choose to instead scale out the existing BI domain.

C: OBIEE Clustering - Approach of Oracle BI Server Load balancing/Failover

B: Example:
1. Configure the new source table to have the 'logical level' under the content set to 'Countries' (the summarized level)

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2. Do the similiar setting for dimension table
Now when user query the data at 'Counties' level, the query will be redirected to these summary table instead of the more detail fact table Note: Aggregate tables are Physical tables that store Aggregates of measures across multiple levels of a Hierarchy.