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Aggregating Data For The Oracle Warehouse

Oracle Tips by Burleson Consulting

The Data Warehouse Development Life Cycle

Aggregating Data For The Oracle Warehouse

Alternate Summary Data Formats

Of course, the other tables are two dimensional--comparing one dimension against the other--but these table definitions can easily be massaged by an application to provide a tabular representation of several dimension attributes. Table 6.2 presents a tabular display of item_type against region, much as a multidimensional database would present these summaries.

                     Clothes        Food           Hardware
West          $113,999     $23,574     $56,335
East           $45,234       $835,342   $66,182
North          $826,463     $43,383     $77,261
South         $1,223         $9,281      $56,392

Table 6.2 region versus type.

But what if management wants to look at quarterly summaries instead of monthly summaries? What about yearly summaries? Of course, this same technique can be used to roll up the monthly summary tables into quarterly summaries, yearly summaries, and so on, according to the demands of end users.

Just as the fact table is time based, aggregate tables can be time based, and the ranges of times can be specified, as shown in the following code:

SELECT SUM(cost*qty), store_id
FROM sale_fact
GROUP BY store_id;

Remember, all data warehouse fact tables are usually ordered by some kind of data, and it makes sense that aggregate tables will also be ordered by a date.

This is an excerpt from "High Performance Data Warehousing", copyright 1997.

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