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Oracle Tips by Burleson Consulting

The Data Warehouse Development Life Cycle

Oracle Data Warehouse Design

In our over-simplified example, we see that level_one can be food or nonfood; level_two can be animal, vegetable, paper, or toy; and level_three can be beef, chicken, or "U" for unclassified (in cases where a level three classification does not apply). The advantage of this representation of the hierarchy is that this representation will only add 3 bytes to each fact row. The downside is that queries are cryptic for end users. End users will have to know the valid values for each classification level in their queries. For example, to query for the total sales of non-food items by customers who earn more than $50,000 per year, would require that they know the proper flag vales as shown below.

SELECT sum(sale_amount) from FACT
yearly_income_class > 3;

2.   Assign a descriptive name for each level in the hierarchy. This method would assign descriptive values for each product class, thereby making it easier for the end users to query the fact table. For example:

food_flag                char(1)
   CONSTRAINT food_check
      CHECK (food_flag in (‘Y’,‘N’);
animal_or_vegtable_flag  char(1)
   CONSTRAINT animal_check
      CHECK (animal_or_vegetable_flag in (‘A’,‘V’,’U’);
type_of_meat_flag        char(1)
   CONSTRAINT meat_check
      CHECK (type_of_meat_flag in (‘F’,‘C’,’P’,’B’);
. . .

      The benefit of this approach is that the queries can be made very descriptive, for example:

yearly_income_class = 2;

The downside, of course, is that there will be many more flags in the fact table, and, because the values are mutually exclusive at each level, most of the flags will contain NULL values. There will also be far more indexes on the fact table, and they will slow down the nightly batch update process. As data warehouses grow into the terabyte range, even a few additional bytes can have a substantial disk cost. Also, the type of front end will also influence the decision about the type of flags. If your application hides the SQL behind a front end query tool, then this type of approach has no real advantage.

Again, these physical attribute representation issues go to the very heart of the data warehouse, and intelligent up front planning will ensure a sound, robust system.

This is an excerpt from "High Performance Data Warehousing".
If you like Oracle tuning, you may enjoy the book Oracle Tuning: The Definitive Reference , with over 900 pages of BC's favorite tuning tips & scripts. 

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