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Data Warehousing and Data Mining

notes Fact Constellation

Sophisticated applications may require multiple fact tables to share dimension tables. This kind
of schema can be viewed as a collection of stars, and hence is called a galaxy schema or a fact
constellation.

Example: A fact constellation schema of a data warehouse for sales and shipping is
shown in the following Figure 10.7.

figure 10.7: fact constellation schema of a Data Warehouse for sales and shipping

Task Discuss the pros and cons of top down and bottom up approaches.

Differences between a Data Warehouse and a Data Mart

In data warehousing, there is a distinction between a data warehouse and a data mart. A data
warehouse collects information about subjects that span the entire organisation, such as customers,
items, sales, assets, and personnel, and thus its scope is enterprise-wide. For data warehouses,
the fact constellation schema is commonly used since it can model multiple, interrelated subjects.
A data mart, on the other hand, is a department subset of the data warehouse that focuses on
selected subjects, and thus its scope is department-wide. For data marts, the star or snowflake
schema are popular since each are geared towards modeling single subjects

introducing concept hierarchies

A concept hierarchy defines a sequence of mappings from a set of low level concepts to higher
level, more general concepts. Consider a concept hierarchy for the dimension location. City
values for location include Lucknow, Mumbai, New York, and Chicago. Each city, however, can
be mapsped to the province or state to which it belongs. For example, Lucknow can be mapped
to Uttar Pradesh, and Chicago to Illinois. The provinces and states can in turn be mapped to
the country to which they belong, such as India or the USA. These mappings form a concept
hierarchy for the dimension location, mapping a set of low level concepts (i.e., cities) to higher
level, more general concepts (i.e., countries). The concept hierarchy described above is illustrated
in Figure 10.8.

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