A conceptual design for high-volume data processing of warehouse database into multidimensional database

Abstract

This paper presents a conceptual model of analyzing huge amount of information from a data warehouse into Multidimensional Database (MDDB) using multidimensional data (MDD)model. The major advantages of this model are: 1) it shows the input-output design phase of MDDB and 2) it reduces workload in high-volume data processing. This conceptual model shows how data catalogs can be used to generate the MDD forms (Dimensions, Variables or data values, and Relative di­mensions) of a multidimensional cube for On-line Analytical Processing (OI.AP). The model may also be expressed by.fact schemes that integrate relative information and external sources, as well as extends the algorithm to build MDD patterns in standard SQL form. This schema is based on the basic elements of an MDD model. This model uses three symbols: center nodes, branch nodes, and rectangles. The center node represents the fastest varying dimension, branch nodes represent associate dimension attributes, and rectangles represent data value indexing and measurements.