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Oracle9i OLAP User's Guide
Release 2 (

Part Number A95295-02
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Building SQL-Based OLAP Applications

SQL-based applications can access multidimensional data, which is stored in analytic workspaces. Two mechanisms in the database's object technology make this possible:

If you overlay the table functions with relational views, then you can make the table functions (and thus the source of the data) transparent to SQL-based applications. Your applications can use standard SQL to run against these views of multidimensional data, the same way that they access other relational tables and views in the database.

See Also:

PL/SQL User's Guide and Reference for detailed information about object types and table functions.

Figure 3-1 shows how a SQL application can access multidimensional data (using table functions and views) as well as relational data.

Figure 3-1 Components of a SQL-Based Analytical Application

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Methods of Accessing Multidimensional Data From SQL

There are several ways that SQL can access the multidimensional data of an analytic workspace. An abstract data type and the table functions underlie all of them. The method that you choose depends on how you want to use the data.

Embedding OLAP DML Commands in SQL

Using the procedures and functions in the DBMS_AW package, SQL programmers can issue OLAP DML commands directly against analytic workspace data. They can move data from relational tables into an analytic workspace, perform advanced analysis of the data (for example, forecasting), and copy data from the analytic workspace back into relational tables.

While the data is in the analytic workspace, SQL programmers can also issue SELECT statements against the data in the analytic workspace using the OLAP_TABLE function.

See Also:

Chapter 11, "DBMS_AW"