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Definition
According to Dr. Kimball, Dimensional Modeling is a design technique for databases intended to support end-user queries in a data warehouse.
Dimensional Design VS Normalized Design
Dimensional Modeling
Normalized Modeling
Reporting and Analysis
Operational Inserts and Updates
Data Warehouse
Transactional Data Source(s)
Transactional System and Normalized Design
Enable consistent and fast writing
Insert or update touch the database in one place
Too complicated for data warehouse queries and performance issue
3NF (third-normal-form)
Normalized Design
Data Warehouse and Dimensional Design
Star schema: when a fact table is joined to a set of dimension tables
Simplicity
Symmetry
Performance benefits
Dimensional Design
Dimension Model Elements: Fact Table
Stores numerical performance measurements
Contains:o Dimension keyso Facts: business measures
Grain: defined by a list of dimensions
3 categories of fact table grains: o Transactiono Periodic snapshoto Accumulative snapshot
Dimensions
Facts
Dimension Model Elements: Fact Table
Looks ‘thin’ in shape
Primary key: subset of the foreign keys
Expresses a many-to-many relationships
Stores textual descriptors
Contains: attributes
Highly denormalized
Represent hierarchical relationships
Looks ‘fat’ in shape
Dimension Model Elements: Dimension Tables
Dimension Model: bring Facts and Dimensions together
Surrogate keys: sequentially assigned integers
Benefits:
o Environment buffer
o Allow data integration
o Support SCD (slow changing dimension)
Dimensional Modeling Design Process
Choose the Business Process
Declare the Grain
Identify the Dimensions
Identify the Facts
Easy to understand
Optimized for performance
Historical tracking of information
Extensible to accommodate changes
Summary
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