1. Data Warehouses, Dimensional Modeling, and the Laundromat

3. The washers and dryers are like an organization’s operational / transaction systems . . .

4. Sorting by color is best for washing, but not for retrieval and wearing!
Reorganize

5. ETL is like bringing clothes home and putting them away for easy retrieval!

6. Denormalized Star Schema – Common Approach
Fact (core or transaction) Tables in middle of star
Dimensional (structural or “lookup”) Tables around “points” of star
Cust # CustName
100 Moe
101 Larry
102 Curly
Loc # LocName
1000 NY
2000 LA
3000 PGH
LOC DIMENSION
CUSTOMER DIMENSION
Order # Date Cust# Prod# Loc#
1 06/15/XX 100 QR
2 07/19/XX 100 QR
3 08/30/XX 101 SR
SALES ORDER (FACT) TABLE
Date Quarter
06/29/XX 2 Bob
06/30/XX 2 Sue
07/01/XX 3
Prod # ProdName
QR22 Rake
SR56 Spade
TW43 Mulch
PRODUCT DIMENSION
DATE DIMENSION
The DW structure reflects Dimensional Modeling

7. Common (Conformed) Dimensions
Denormalized Star Schema (continued) Stars are linked via common (i.e., Conformed) Dimensions to form Data Warehouse
Cust # CustName
100 Moe
101 Larry
102 Curly
Loc # LocName
1000 NY
2000 LA
3000 PGH
LOC DIMENSION
CUSTOMER DIMENSION
Order # Date Cust# Prod# Loc#
1 06/15/XX 100 QR
2 07/19/XX 100 QR
3 08/30/XX 101 SR
ORDER TABLE
SALES ORDER (FACT) TABLE
Common (Conformed) Dimensions
Date Quarter
06/29/XX 2
06/30/XX 2 S
07/01/XX 3 Juan
CUSTOMER TABLE
Prod # ProdName
QR22 Rake
SR56 Spade
TW43 Mulch
PRODUCT DIMENSION
DATE DIMENSION
TIME
Prod# ProdName Stock Date Units
QR22 Rake 03/23/XX
TW43 Mulch 04/15/XX 1452
SR56 Spade 05/01/XX
INVENTORY (FACT) TABLE

8. DW Development Approaches
Inmon Model: EDW approach (top-down)
Kimball Model: Data mart approach  (bottom-up)
Which model is best? Depends

9. Bill Inmon (Top-Down)
Build an all-encompassing Enterprise Data Warehouse (EDW)
When EDW is finished, use it to create subject-oriented Data Marts
“Cargo-Ship” approach

10. Ralph Kimball (Bottom-Up)
Build subject-oriented Data Marts first
Connect the individual Data Marts to create a Data Warehouse
Start small and add to Data Warehouse over time
“Freight Train” approach

11. Best Approach depends on the organization’s resources and needs!

12. In-Memory Visualization Tools
Newest End-User Data Analytic Tools
Very visual dashboards displays and gauges
Stores data in local PC’s RAM (more flexible & faster performance)
Can utilize Dimensional Modeling of a Data Warehouse, or model data on local PC
Main competitors: Tableau, Qlikview, MS-Power BI

13. MS Power BI Demo