star schema v. snowflake schema 1

[Guest_imported]

Well, needless to say I am delving into unchattered territory of data warehousing.
Can any good soul please explain to me in detail (if possible) the differences between star schema and snowflake schema.
thank you!
toaft

 

[tdatgod]

Hi,
you might want to check out the teradata Documentation. We have a whole manual dedicated to Database design.

teradata Documentation is available at.

http://www.info.ncr.com/sd/sd-1.cfm?page=td

Under titles in the middle of the page click on

Database design.

Select the version from 4.1 which is our current release.

Chapter 5 has a description of the normalization process and has a description of the Star Schema and Snowflake schema.

looking at the pictures a snowflake schema is a way to join multiple Star Schemas off a common dimension.

Which is best I don't know. That is why Consultants get paid the big bucks. I am just a lowly programmer.

 

[Guest_imported]

Thanks for the useful information.
I am sorting through it.
Thanks (again)
toaft

 

[keefy]

A snowflake, to put it in simple terms, is an extension of a star schema.

Where in a star schema each dimension is typically stored in one table (which could therefore contain hundreds of attributes), the snowflake principle extrapolates this dimension and creates tables for each level of that dimensional hierarchy.
In other words, a Region dimension may contain the levels Street, City, State and Country. In a star schema, all these attributes would be stored in one table (typically given the name 'region_dim'), whereas the snowflake approach would create 'street_dim', 'city_dim', 'state_dim' and country_dim', each containing their respective attributes and unique identifiers (used to join the tables together).

It is often thought that a snowflake schema makes for a better data storage model, but it typically results in longer response times for any application wishing to extract the data.

I hope that helps...