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A. Potocka:
"Webbasierte Darstellung großer Datenmengen als pivot-tabelle mithilfe ressourcenoptimierter Aggregationsverfahren";
Supervisor: G. Raidl, M. Gruber; Institut für Computergraphik und Algorithmen, 2008; final examination: 2008-10.

A pivot table is a complex, multidimensional table which makes it possible to
analyse data comparing more than one attribute at the same time. Creating
pivot tables with huge amounts of analysed data is not only a question of
time. Limits concerning the memory capacity are often reached. The growing
demand for platform independence and web based applications without high
license costs is also an important criterion. These requirements cannot be
supplied by existing solutions.
In this thesis four methods for creating a pivot table out of a database
table are presented. They differ in the amount of SQL queries needed, the
complexity of the operations and how much cache is used for storing the SQL
results. These factors are of main interest when discussing the computational
results. For choosing the appropriate method also the kind and the amount
of the analysed data to be presented in a pivot table have to be considered.