1. Role Playing Dimensions (p. 223-226)
Consider a DM where we are tracking claims as they make their way through processing to payment or refusal
We can track the date received, the date the accident occurred, the date of adjustment, the date of payment, as well as the policy holder, the policy, the claimed amount, the paid amount
Accident Date
Adjustment Date
Receipt Date
facts
Payment Date
Policy Holder
Policy
March, 2003
Ron McFadyen

2. Role Playing Dimensions
A dimension appears several times, in different roles.
We need to implement the dimension once, and reference it via several FKs.
One must be careful with the SQL when retrieving data
Recommendation to use SQL Views – one per role
Accident Date
Adjustment Date
Receipt Date
facts
Payment Date
Policy Holder
Policy
March, 2003
Ron McFadyen

3. Many-to-one-to-many traps (p. 222-223, 252-254)
A conformed dimension allows us to bring data together from multiple fact tables, or from multiple data marts.
Query: For each day in July and for each product, how many did we sell and how many did we have in stock?
Store
Sales Facts
Product
Date
Inventory Facts
Supplier
Warehouse
March, 2003
Ron McFadyen

4. Many-to-one-to-many traps
Doing this in one query will likely lead to errors (why?)
Recommended procedure: drill across the fact tables using multipass SQL
With multipass SQL each fact table is queried separately and then the individual results are merged.
Store
Sales Facts
Product
Date
Inventory Facts
Supplier
Warehouse
March, 2003
Ron McFadyen

5. Time of Day Dimension (p. 245-246)
Time of day normally reduces to a degenerate dimension where the time of day value is stored in the fact table
Product
Time
Production Facts
Date
Crew
Production Facts
DateId
ProductId
CrewId
TimeOfDay
Physical Fact table
Degenerate dimension
Actual time of day stored
March, 2003
Ron McFadyen

6. Value banding (p )
Flexible reporting is provided by joining to a band table via non-equi join
Band table
Band_group_name
Band name
Band sort number
Band metric lower value
Band metric upper value
Facts
metric
>=
<
March, 2003
Ron McFadyen

7. Group 3. Implementation of a
Assignments
Two assignments due by April 4. Choose any two from two different groups
Group 1.
ETL for populating the NorthWind Dimensional Model. This must use DTS.
Implementation of the algorithm to maintain a Type II dimension
Group 2. Description of a
Kimball Design tip
Dimensional Friendly Criteria
Group 3. Implementation of a
Navigational Bridge
Value banding
Role-playing
3-4 pages, incorporate examples, diagrams
Accompanied by a 1 page description
March, 2003
Ron McFadyen

8. Assignments
Group 4.
Design and implement a DM for the UW. Must include plans for at least 2 fact tables and aggregation. Include a logical model and a SQL Server or Access implementation. ETL not required. Describe the type of analyses the model facilitates.
March, 2003
Ron McFadyen