Data Warehouses, Dimensional Modeling, and the Laundromat

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Presentation transcript:

Data Warehouses, Dimensional Modeling, and the Laundromat

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

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

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

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 QR22 1000 2 07/19/XX 100 QR22 1000 3 08/30/XX 101 SR56 2000 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

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 QR22 1000 2 07/19/XX 100 QR22 1000 3 08/30/XX 101 SR56 2000 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 150 TW43 Mulch 04/15/XX 1452 SR56 Spade 05/01/XX 997 INVENTORY (FACT) TABLE

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

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

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

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

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

MS Power BI Demo