Bus Architecture

Value Chain

• Identifies the natural logical flow of an organization’s primary activities

• Operational source systems produce snapshots at each step of the value chain which in turn generates metrics

• Metrics translate to several fact tables and analysis of these give better evaluation of overall performance

Value Chain

Retailer issues purchase order

Retail store sales

Retail store inventory

Deliveries at retail store

Retailer warehouse inventory

Deliveries at retailer warehouse

Integration

• Needs of high-level managers use data generated across business processes

• Example: customer relationships from end to end perspective– Quotes, orders, invoicing, payments,

customer service

• Consistent data

Integration

Bus Architecture

• Standard that allows for implementing different data marts by different groups at different times

• Provides rational approach to decomposing the enterprise data warehouse planning task

• Tech design tool, pm tool, com tool• Integrated with value chain

Bus Architecture

DW Bus Matrix

DW Bus Matrix

• Rows– Data marts

• Columns– Dimensions

• X– Dimensions belonging to data marts

Integrating stovepipes

• Honest appraisal of non-integrated data marts– Gap analysis between stovepipe environment

and DW architected goal

• Develop incremental plan to integrate stovepipe into DW

• Sell internally as it will use resources and need commitment

• Be prepared for the possibility of scrapping stovepipe

Conformed Dimensions

• Identical or strict mathematical subset of most granular detailed dimension

• The following are consistent: – dimension keys– attribute column names – attribute definitions – attribute values

• Replicated either physically or logically throughout enterprise

• Built in staging area

Conformed Dimensions: Flavors

• Exact same dimension– Date dimension connected to sales fact

is same as the date dimension connected to inventory fact

– May also be same physical table in DB

• Same level of detail but only subset of rows– Product rows only pertaining to

particular part of user’s business

Conformed Dimensions: Flavors

• Roll-up dimensions– Different

granularity– Attributes

common to both detailed and rolled-up tables should be labeled, defined, and valued identically

Product Dimension

Product Key (PK) Product key SKU number (Natural Key) Brand description Category description Department description Package type description Package size Fat content Diet type Weight Weight units of measure Storage type Shelf life type Shelf width Shelf height Shelf depth etc...

Brand Dimension

Brand Key (PK) Brand description Category description Department description

Dimension Authority

• Responsible for each conformed dimension

• Define, maintain, and publish particular dimension and subsets to data marts

• Stage dimension data

Conformed Facts

• In general fact table data is not explicitly duplicated in multiple data marts

• In case there is need, then underlying definitions, equations, and units of measure for facts must be the same if these are to be called the same name