• Building an Oracle OLAP Analytic Workspace

    Building an Oracle OLAP Analytic WorkspaceThe previous my article focused on designing OLAP applications. In this article, we walk you through the steps required to build an Oracle OLAP analytic workspace. Recall that an Oracle OLAP analytic workspace contains a collection of dimensions and a collection of cubes, where any given cube contains only the dimensions required to describe the measures in that cube. The analytic workspace also holds other multidimensional objects, such as folders and programs, that are required for an OLAP analysis.

  • Designing an Oracle OLAP Analytic Workspace

    Oracle OLAP Design Process in Analytic Workspace Analytic WorkspaceIn this section, we discuss the features in Oracle OLAP that you should be aware of when designing analytic workspaces. The content here expands on the concepts introduced in our blogs (where those concepts relate to design) and the general design principles discussed in the preceding section. 


    Determining Dimensions from user Requirements

    As mentioned, user requirements must drive the design of Oracle OLAP cubes. This fact is often overlooked in Oracle OLAP design, as the data is sourced from relational tables or views. Often, these tables are part of a data warehouse with a well-defined structure. The structure of the source tables will be an important influence, but the ultimate structure of the OLAP cubes should be driven by user requirements, not the convenience of loading data from the data warehouse, because often the data warehouse design is not reflective of user requirements. Oracle OLAP cubes can be used solely for their cube-organized materialized views to accelerate performance of queries on data warehouses, but they offer much more.