Explanation/Reference:
Screenshot below.

It is a best practice to create aliases for all tables. Aliases are created in the Physical Layer of the repository. Some of the benefits of using aliases are given below: (A) * An alias is used to avoid circular joins and to configure self joins.
*You can create a join relationship which is different than the actual foreign key relationship in the database. This helps in defining relationships to meet business model criteria.
*Aliases can function in numerous ways to define business model e.g. a table can act both as a dimension and a fact using aliases.
(B) * You can rename aliases to make physical and business model easier to understand.

Steps for Creating Aggregate Tables in OBIEE
1.Create all Dimension Tables, Fact Tables & Hierarchies, which are required to be aggregated.
2.Go to ToolsaUtilities (from Administration tool menu bar), a dialog box will pop up with all available utilities.
3.Select Aggregate Persistence Wizard, and then click Execute Button.
4.Now Select appropriate path where you need to generate Aggregate Table SQL.
Note : Click Generate DDL file for first time generation of Aggregate Table
Click Next, to move to next page (Select Business Model & Measure Page)
In Select Business Model & Measure Page, Select Appropriate Business Model & then select
associated Fact / Measure.

Etc.

A:
*Combining Relational and OLAP Data Sources: Oracle's Common Enterprise Information Model allows users to combine data from a relational system and an OLAP source in a single calculation.
For example, a user can compare sales forecasts from an Oracle CRM System with budget data from an Oracle Essbase planning application. To clients of the Common Enterprise Information Model, the forecast and budget data appear to be from the same logical source.
*The Essbase server provides advanced multi-user read and write capabilities, including data
update and multi-user recalculation. Business users with front-end tools can write data back to a
server and recalculate the data on a server using calculation scripts-key functionality to support
sophisticated modeling and planning applications.
*Using aggregate storage, Essbase serves a wide range of analytic needs-financial analysis,
planning, budgeting, sales analysis, marketing analysis, supply-chain analysis, and profitability
analytics-all from a single analytic infrastructure.
B:
Note: The Analytic Data Model (ADM) is an API used to access OLAP data and metadata. ADM is
similar to JDBC, providing a single common API that hides most differences between OLAP data
sources.
Note 2: Data model for business intelligence The most important component of business intelligence is the concept of 'data model'. data model determinde what kind of analysis that end user could do with the data. It is also an independant concept that could span across different vendor 's product.
Unlike data model of the transaction system, the typical analytic data model is often denormalized and store extra data for analytic query and better query performance while transaction data model use is often normalized and optimized for a few data read and write, which is implemented by jointing many tables.
The most common used analytic data model in business intelligence is call the 'Star schema' data model.
With the Oracle business intelligence system, We could define star schema and dimension data model in the 'logical layer' in the admin tools. The data model in OBIEE could span different data source in physical layer, which means OBIEE have the capability of building one logical data model which is actually connect to different database in the backend