Modeling and Querying Multidimensional Data Sources in Siebel Analytics: Kazi A. Zaman and Donovan A. Schneider   View Paper (PDF)   Return to Query processing (Industrial) Abstract Large organizations have a multitude of data sources across the enterprise and want to obtain business value from all of them. While the majority of these data sources may be consolidated in an enterprise data warehouse, many business units have their own data marts where analysis is carried out against data stored in multidimensional data structures. It is often critical to pose queries which span both these sources. This is a challenge since these sources have differing models and query languages (SQL vs MDX). The Siebel Analytics Server enables this requirement to be fulfilled. In this paper, we describe how the multidimensional metadata is modeled relationally within Siebel Analytics, efficient SQL to MDX translation algorithms and the conversion protocols required to convert a multidimensional result into a relational rowset. ©2006 Association for Computing Machinery