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Exercise No. 16: Workout (log)

This cube stores data about athletes doing workouts.

We have four dimensions with the following hierarchical structure:

Table L.E.55.1 - workout

"Number of workouts" is the only key figure. Each athlete has an attribute A_at_dob, the date of birth, and each personal coach has his address ("P_pc_ad") as an additional attribute.

Please draw the Classic Star and the Fact Constellation Schema. Then draw the dimension tables partitioned and normalized and use them to build a Snowflake Schema!

Solution

This case's Classic Star Schema has five tables, a central fact table and four dimension tables. The latter consist of a generated key as well as a key and a text field for each hierarchy (except the total aggregation) and the level attribute. The fact table uses the generated keys from the dimension tables as a combined key and contains the key figure "no. of workouts":

Figure L.E.55.1 - The Classic Star Schema

The Fact Constellation Schema for this case consists of four dimension tables and 12 fact tables (1x2x2x3):

Figure L.E.55.2 - The Fact Constellation Schema

Partitioning the Classic Star's dimension tables by the level attribute results in one table for each hierarchy level (in each dimension). All tables include the fields of the higher levels, the level attribute itself is omitted:

Figure L.E.55.3 - DT partitioned (left) and normalized (right)

Normalizing the dimension tables completely means that only the key of the next higher level is kept in each table. Please note that the tables for the total aggregation level have been neglected in Figure L.E.55.3.

The Snowflake Schema is a combination of the Fact Constellation Schema's fact tables and the dimension tables either partitioned or normalized (in this case partitioned):

Figure L.E.55.4 - The Snowflake Schema

This exercise is part of a case study: dfm - apa - log

Exercises List