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 91.4904 Ron McFadyen

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 91.4904 Ron McFadyen

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 91.4904 Ron McFadyen

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 91.4904 Ron McFadyen

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 91.4904 Ron McFadyen

Value banding (p. 251-252) 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 91.4904 Ron McFadyen

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 91.4904 Ron McFadyen

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 91.4904 Ron McFadyen