Data Warehouse Concepts - Data Warehouse Systems: Design and Implementation - page 82

In addition, several design tools are provided, which are described next:
￿ Pentaho Schema Workbench provides a graphical interface for design-
ing OLAP cubes for Mondrian. The schema created is stored as an XML
file on disk.
￿ Pentaho Aggregation Designer operates on Mondrian XML schema
files and the database with the underlying tables described by the schema
to generate precalculated, aggregated answers to speed up analysis work
and MDX queries executed against Mondrian.
￿ Pentaho Metadata Editor is a tool that simplifies the creation of
reports and allows users to build metadata domains and relational data
models. It acts as an abstraction layer from the underlying data sources.
3.7 Summary
In this chapter, we introduced the multidimensional model, which is the
basis for data warehouse systems. We defined the notion of online analytical
processing (OLAP) systems as opposite to online transaction processing
(OLTP) systems. We then studied the data cube concept and its components:
dimensions, hierarchies, and measures. In particular, we presented several
classifications of measures and defined the notions of measure aggregation
and summarizability. Then, we defined a set of OLAP operations, like roll-
up and drill-down, that are used to interactively manipulate a data cube.
We then described data warehouse systems and highlighted their differences
with respect to traditional database systems. As data warehouse systems
include many different components, we discussed the basic architecture of
data warehouse systems and several variants of it that may be considered.
We finished this chapter by giving an overview of two representative sets of
tools: Microsoft SQL Server tools and Pentaho Business Analytics.
3.8 Bibliographic Notes
Basic data warehouse concepts canbefoundintheclassicbooksby
Kimball [ 103 ]andbyInmon[ 90 , 91 ]. In particular, the definition of data
warehouses we gave in Sect. 3.3 is from Inmon.
The notion of hypercube underlying the multidimensional model was
studied in [ 72 ], where the ROLLUP and the CUBE operations were defined
for SQL. Hierarchies in OLAP are studied, among other works, in [ 22 , 123 ].
The notion of summarizability of measures was defined in [ 115 ] and has been
studied, for example, in [ 84 - 86 ]. Other classification of measures are given in