TRENDS IN DATABASE TECHNOLOGY - Database Design and Development: An Essential Guide for IT Professionals - page 654

PRESENTATION
LAYER

Desktop
Client

MDBMS
Server

MOLAP
Engine

MDDB

APPLICATION
LAYER

Data
Warehouse

RDBMS
Server

DATA
LAYER

Figure 20-16 The MOLAP model.

OLAP Models OLAP systems provide multidimensionality in one of two ways:
multidimensional OLAP and relational OLAP. The method of storing data differ-
entiates the two methods. We will now examine these two methods.

The MOLAP Model In the multidimensional OLAP (MOLAP) model, data for
analysis are stored in specialized multidimensional databases. Large multidimen-
sional arrays form the storage structures. For example, to store sales number of
500 units for product ProductA, in month number 2001/01, in store StoreS1, under
distributing channel Channel05, the sales number of 500 is stored in an array rep-
resented by the values (ProductA, 2001/01, StoreS1, Channel05).
The array values indicate the location of the cells. These cells are intersections
of the values of dimension attributes. If you note how the cells are formed, you will
realize that not all cells have values of metrics. If a store is closed on Sundays, then
the cells representing Sundays will all be nulls.
Let us now consider the architecture for the MOLAP model. Please go over each
part of Figure 20-16 carefully.
Note the three layers in the multitier architecture. Precalculated and prefabri-
cated multidimensional data cubes are stored in multidimensional databases. The
MOLAP engine in the application layer pushes the multidimensional view of the
data from the MDDBs to the users.
Multidimensional database management systems are proprietary software
systems. These systems provide the capability to consolidate and fabricate summa-
rized cubes during the process that loads data into the MDDBs from the main data
warehouse. The users who need summarized data enjoy fast response times from
the preconsolidated data.