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Data Warehousing and Data Mining

notes
figure 2.4: eight views of Data cubes for sales information

For example, a relation with the schema “sales(part; supplier; customer; sale price)” can be
materialised into a set of eight views as shown in Figure 2.4, where psc indicates a view consisting
of aggregate function values (such as total sales) computed by grouping three attributes part,
supplier, and customer, p indicates a view consisting of the corresponding aggregate function
values computed by grouping part alone, etc.

2.6.5 transaction Database

A transaction database is a set of records representing transactions, each with a time stamp,
an identifier and a set of items. Associated with the transaction files could also be descriptive
data for the items. For example, in the case of the video store, the rentals table such as shown in
Figure 2.5, represents the transaction database. Each record is a rental contract with a customer
identifier, a date, and the list of items rented (i.e. video tapes, games, VCR, etc.). Since relational
databases do not allow nested tables (i.e. a set as attribute value), transactions are usually stored
in flat files or stored in two normalised transaction tables, one for the transactions and one for
the transaction items. One typical data mining analysis on such data is the so-called market
basket analysis or association rules in which associations between items occurring together or in
sequence are studied.

figure 2.5: fragment of a transaction Database for the rentals at our video store

Rental
Transaction ID Date Time Customer ID Item ID
T12345 10/12/06 10:40 C12345 11000

2.6.6 advanced Database systems and advanced Database applications

With the advances of database technology, various kinds of advanced database systems
have emerged to address the requirements of new database applications. The new database
applications include handling multimedia data, spatial data, World-Wide Web data and the
engineering design data. These applications require efficient data structures and scalable methods

28 LoveLy professionaL university