Example: Aggregation & Customization from the Virtual University

Simple reporting: Weekly Usage Statistics by int. and ext. Users

OLAP: Queries that take long with RDBMS and SQL (multiple joins) are fast and easy with OLAP-cubes (or the denormalized Star schema).

Operations: Roll-up, drill-down, slice, dice, pivot

Source data (from the data warehouse)

[Mon Dec  3 13:53:12 2001] "wu01_4da" "" 
"session=wu01_session230f1-1007383972" "137.208.3.45"

Aggregated data by session

ID := {wu01_session2246d-1006862104}
date := {Tue Nov 27 12:55:46 2001}
mediation := {wu01_290a;wu01_30e3;wu01_35af;wu01_4d1;
wu01_4bf;wu01_4c1;wu01_a57;wu01_26b9;wu01_c69;wu01_419;
wu01_11a8;wu01_114;wu01_364d;wu01_3396;wu01_2e1a}
user := {myvu4e1245bef9-1006862431}

Index: Contents