Snowflake
Schema
Need to create a snowflake
schema for an information management project and want an overview of
key design considerations?
What is a
data mart?
Data
marts are a critical part of data warehouse design. They are created to
store data required for analysis by specific departments e.g.
manufacturing department, sales department or inventory control.
Data
is extracted from the warehouse and transformed into facts and
dimensions within a data mart, which is then queried using client tools
or business intelligence reporting tools.
What is a
star schema dimension design?
A
star dimension is a de-normalized structure, which means that redundant
data is stored in the dimension table to help with query performance.
Sample Star Design
In the sample above, the description North America is repeated every
time that region code 10 occurs e.g.
| Sales
Territory ID |
Region
Code |
Region
Description |
| 1 |
10 |
North
America |
| 2 |
10 |
North
America |
| 3 |
20 |
South
America |
A query for North America will return all rows that contain North
America for all facts associated with region code 10.
What is a
snowflake?
A
snowflake dimension is a normalized structure, which means that
redundant data is not stored in the dimension table, but is stored in
the snowflake to help with performance e.g.
Sample Snowflake
Snowflake design can be used to:
- Reduce
dimension data storage requirements, however, since dimensions have
very low volumes of data, this is not really an important
consideration; and
- Improve reporting performance for some business
intelligence query tools, which prefer snowflake designs.
Summary...
A
snowflake design is sometimes used to improve performance and should be
considered if required by specific business intelligence reporting
tools.
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