Basic Model: Retail Grocery
Store
 Process: Retail Sales
 Grain: POS line item
 Dimensions: Date, Store, Product, Promotion
 Facts: Sales Quantity, Sales Dollar Amount,
Cost Dollar Amount, Gross Profit Dollar
Amount.

Model
DATE
DateKey
Attributes
STORE
StoreKey
Attributes
POS FACT
DateKey
ProductKey
StoreKey
PromotionKey
POSTransactionNumber
SalesQuantity
SalesDollarAmount
CostDollarAmount
GrossProfitDollarAmount
PRODUCT
ProductKey
Attributes
PROMOTION
PromotionKey
Attributes

Possible Date Attributes










SQL date
Full date description
Day of week
Day of month
Day of calendar year
Day of fiscal year
Month of calendar year
Month of fiscal year
Calendar Quarter
Fiscal Quarter











Fiscal week
Year
Month
Fiscal year
Holiday ?
Holiday name
Day of holiday
Weekday ?
Selling season
Major event etc.

Possible Product Attributes
 Description
 SKU number
 Brand description
 Department
 Package type
 Package size
 Fat content
 Diet type
 Weight
 Weight units of measure
 Storage type
 Shelf unit type
 Shelf width
 Shelf height
 Shelf depth
 etc.

Possible Store Attributes
 Store Name
 Store Number
 Street address
 City
 County
 State
 Zip
 Manager
 District
 Region
 Floor plan type
 Photo processing type
 Financial service type
 Square footage
 Selling square footage
 First open date
 Last remodel date
 etc.

Possible Promotion Attributes
 Promotion name
 Price reduction type
 Promotion media
 Ad type
 Ad agency
 Display type
 Coupon type
 Promotion cost
 Begin date
 End date
 etc.

Factless Fact Tables
In order to evaluate promotions that might have generated no sales we need another approach.
 Promotion could generate another fact table
(or could be considered a fact table in itself).
That new fact table would have no additive attributes.

Conformed Dimensions:
Inventory Snapshot Model
 Process: Store inventory
 Grain: Daily inventory by product and store
 Dimensions: Date, product, store
 Fact: quantity-on-hand

Dimensional Model
DATE
DateKey
Attributes
Inventory Fact
ProductKey
DateKey
StoreKey
QuantityOnHand
QuantitySold
ValueAtCost
ValueAtSellingPrice
PRODUCT
ProductKey
Attributes
STORE
StoreKey
Attributes
Note: QuantityOnHand is semi-additive.
It is additive across product and store, but not across date. The other attributes are additive.

Conformed Dimensions
Common dimensions for different processes should be the same.
 Note: Dimensions for roll-up or aggregated fact tables my add or eliminate attributes based on the aggregation Where attributes apply, they should mean the same thing.

The Bus Matrix
Date Product Store Promotion Warehouse Vendor Contract Shipper
Process
Retail Sales X
Retail Inventory X
Retail
Deliveries
X
Warehouse
Inventory
X
Warehouse
Deliveries
X
Purchase Orders X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X X X

Slowly Changing Dimensions
Attributes in a dimensional table that change over time. Three approaches
Type 1: overwrite the old value
Type 2: create a new dimensional record
Type 3: create a “previous value” attribute

Examples
Original
ProductKey Description Category
21553 LeapPad Education
Type 1
ProductKey
21553
Description Category
LeapPad Toy
Type 2
ProductKey
21553
44631
Description Category
LeapPad Education
LeapPad Toy
Type 3
ProductKey
21553
Description Category
LeapPad Toy
Hybrid
ProductKey
21335
44631
68122
Description Category
LeapPad Electronics
LeapPad
LeapPad
Electronics
Education
SKU
LP2105
SKU
LP2105
SKU
LP2105
LP2105
OldCat SKU
Education LP2105
OldCat SKU
Education LP2105
Toy LP2105
Electronics LP2105

More about dimensions
 Views for dimensions used for different purposes
 e.g. StartDate and EndDate
 Junk dimensions for flags and miscellaneous categories removed from the fact table
 Degenerate dimensions have no attributes
 Usually reserved for order number or something similar

Accumulation Snapshot
 State change summary that has one row per item.
 Access rows on each update.

Multiple Granularities
 Product sales vs. Annual quota
 Line item cost vs. Order shipping cost