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time dimension from month to quarter, or, say, drill down along the location dimension
from country to city.
Concept hierarchies can be used to generalize data by replacing low-level values
(such as “day” for the time dimension) by higher-level abstractions (such as “year”),
or to specialize data by replacing higher-level abstractions with lower-level values.

4.3 Data Warehouse Design and Usage

“What goes into a data warehouse design? How are data warehouses used? How do data
warehousing and OLAP relate to data mining?” This section tackles these questions. We
study the design and usage of data warehousing for information processing, analyti-
cal processing, and data mining. We begin by presenting a business analysis framework
for data warehouse design (Section 4.3.1). Section 4.3.2 looks at the design process,
while Section 4.3.3 studies data warehouse usage. Finally, Section 4.3.4 describes multi-
dimensional data mining, a powerful paradigm that integrates OLAP with data mining
technology.

4.3.1 A Business Analysis Framework for Data
Warehouse Design
“What can business analysts gain from having a data warehouse?” First, having a data
warehouse may provide a competitive advantage by presenting relevant information
from which to measure performance and make critical adjustments to help win over
competitors. Second, a data warehouse can enhance business productivity because it is
able to quickly and efficiently gather information that accurately describes the organi-
zation. Third, a data warehouse facilitates customer relationship management because it
provides a consistent view of customers and items across all lines of business, all depart-
ments, and all markets. Finally, a data warehouse may bring about cost reduction by
tracking trends, patterns, and exceptions over long periods in a consistent and reliable
manner.
To design an effective data warehouse we need to understand and analyze busi-
ness needs and construct a business analysis framework. The construction of a large
and complex information system can be viewed as the construction of a large and
complex building, for which the owner, architect, and builder have different views.
These views are combined to form a complex framework that represents the top-down,
business-driven, or owner’s perspective, as well as the bottom-up, builder-driven, or
implementor’s view of the information system.
Four different views regarding a data warehouse design must be considered: the top-
down view, the data source view, the data warehouse view, and the business query view.