ROLAP can be applied both as a powerful DSS product, as well as to aggregate and pre-stage multi-dimensional data for MOLAP environments. ROLAP products optimize data for multi-dimensional analysis using standard relational structures. The advantage of the MOLAP paradigm is that it can natively incorporate algebraic expressions to handle complex, matrix-based analysis. ROLAP, on the other hand, excels at manipulating large data sets and data acquisition, but is limited to SQL-based functions. Since all organizations will require both complex analysis and analysis of large data sets, it could be necessary to develop an architecture and set of user guidelines that will enable implementation of both ROLAP and MOLAP where each is appropriate.