Intelligent Enterprise

This is especially true when you consider the entire scope of relational technology currently focused on multidimensional data management, including:

• Database kernel support optimized to address multidimensional queries
• RDBMS technology such as Materialized Query/View Tables used to improve performance
• Metadata capture and management of multidimensional structures (for example, dimensions) supported in the relational environment
• Expanded OLAP-centric SQL vocabulary standardized for consistent application.

Database-resident OLAP functions, coupled with these multidimensional solutions offer the possibility of a single point of truth and efficient management of enterprisewide, traditional relational and multidimensional data requirements. We don't need to completely eliminate OLAP-only technology, but certainly minimize the needed investment to only true value-add.

Vendors Taking Note

The OLAP-centric words I've illustrated are consistent in RDBMS products such as DB2, Oracle, and Microsoft SQL (2005). The significance should be obvious: OLAP has been integral to the leading database vendors and continues to influence subsequent product releases. As such, these RDBMS products are capable of serving up data for multiple purposes, including OLAP.

For BI architects, this flexibility translates into significant architectural opportunities that go beyond building and propagating proprietary OLAP structures. Instead, architects can commission their relational database of choice as the frontline of dimensional data. In that capacity, the RDBMS controls the data space and its language, SQL, quietly begins to establish itself as the underlying language of choice.

Michael L. Gonzales is the president of The Focus Group Ltd., a consulting firm specializing in data warehousing. He has written several books, including IBM Data Warehousing (Wiley, 2003). He speaks frequently at industry user conferences and conducts data warehouse courses internationally.