Designing and developing Business Process dimensionalModel or Data Warehouse

About MeSlava Kokaev – Lead Business Intelligence Architect

at Industrial DefenderBoston BI USER GROUP leader

email: vkokaev@bosto

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Business Process Dimensional Modelor “Star Schema” Database

DimensionsDimensions are the foundation of the dimensional model, describing the objects of the business, such as employee, product, customer, service.They describe the surrounding measurement events. The business processes (facts) or actions of the business in which the dimensions participate. Each dimension table links to all the business processes in which it participates.

Fact TablesEach fact table contains the measurements associated with a specific business process. A record in a fact table is a measurement, and a measurement event can always produce a fact table record. These events usually have numeric measurements that quantify the magnitude of the event, such as quantity ordered, sale amount, or call duration. These numbers are called facts (or measures in Analysis Services).

Surrogate KeysPrimary key purpose

Identifies uniqueness

Relates to foreign keys in a fact table

Two candidates

Business key Represents source primary key

Surrogate keyConsolidates multiple data sources

Consolidates multi-value business keys

Allows tracking of dimension history

Limits fact table width for optimizationUsing a surrogate key

is considered best practice

Surrogate Keys Implementation

MS-1981163MS-1981

Source OLTP Table Target DW Table

Surrogate Key

Business Key

Best Practices

SnowflakingSnowflaking is the practice of connecting lookup tables to fields in the dimension tables. Sometimes it's easier to maintain a dimension in the ETL process when it's been partially normalized or snowflaked.

Reviewing Star Schema Benefits • Transforms normalized data into a

simpler model• Delivers high-performance queries• Delivers higher performing queries

using Star Join Query Optimization• Uses mature modeling techniques

that are widely supported by many BI tools

• Requires low maintenance as the data warehouse design evolves

OLTP vs. OLAP

Normalized(OLTP)

Denormalized (Star Schema)

Slowly Changing DimensionsSupport primary role of data warehouse to describe the past accurately

Maintain historical context as new or changed data is loaded into dimension tables

Slowly Changing Dimension (SCD) types

Type 1: Overwrite the existing dimension record

Type 2: Insert a new ‘versioned’ dimension record

Type 3: Track limited history with attributes

The concept of Slowly Changing Dimensions was introduced by Ralph Kimball

Slowly Changing Dimensions Type 1

Existing record is updated

History is not preserved

LastName update to Valdez-Smythe

Slowly Changing Dimensions Type 2

Existing record is ‘expired’ and new record inserted

History is preserved

Most common form of Slowly Changing Dimension

SalesTerritoryKey update to 10

Slowly Changing Dimensions Type 2

Existing record is updated

Limited history is preserved

Implementation is rare

SalesTerritoryKey update to 10

DEMO

ResourcesSQL Server 2008 Books Online,msdn2.microsoft.com/en-us/library/bb543165(sql.100).aspx

The Microsoft Data Warehouse Toolkit by Joy Mundy, Warren Thornthwaite, and Ralph Kimball

The Data Warehouse Lifecycle Toolkit by Ralph Kimball, et al.