In Dimensional modeling fact table is normalized or denormalized?in case of star schema and incase of snow flake schema?

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Karthik

  • Dec 15th, 2005
 

Star schmea--De-Normalized Dimesions

Snow Flake Schema-- Normalized dimesions

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Deepak Sukheja

  • Dec 16th, 2005
 

no concept of naomailzation in the case of star schema but in the case of snow flack schema dimension table must be normalized.

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bvrp

  • Dec 18th, 2005
 

In Dimensional modeling, Star Schema: A Single Fact table will be surrounded by a group of Dimensional tables comprise of de- normalized data Snowflake Schema: A Single Fact table will be surrounded by a group of Dimensional tables comprised of normalized dataThe Star Schema (sometimes referenced as star join schema) is the simplest data warehouse schema, consisting of a single "fact table" with a compound primary key, with one segment for each "dimension" and with additional columns of additive, numeric facts.The Star Schema makes multi-dimensional database (MDDB) functionality possible using a traditional relational database. Because relational databases are the most common data management system in organizations today, implementing multi-dimensional views of data using a relational database is very appealing. Even if you are using a specific MDDB solution, its sources likely are relational databases. Another reason for using star schema is its ease of understanding. Fact tables in star schema are mostly in third normal form (3NF), but dimensional tables in de-normalized second normal form (2NF). If you want to normalize dimensional tables, they look like snowflakes (see snowflake schema) and the same problems of relational databases arise - you need complex queries and business users cannot easily understand the meaning of data. Although query performance may be improved by advanced DBMS technology and hardware, highly normalized tables make reporting difficult and applications complex.The Snowflake Schema is a more complex data warehouse model than a star schema, and is a type of star schema. It is called a snowflake schema because the diagram of the schema resembles a snowflake.Snowflake schemas normalize dimensions to eliminate redundancy. That is, the dimension data has been grouped into multiple tables instead of one large table. For example, a product dimension table in a star schema might be normalized into a products table, a Product-category table, and a product-manufacturer table in a snowflake schema. While this saves space, it increases the number of dimension tables and requires more foreign key joins. The result is more complex queries and reduced query performance.

sreenu

  • Dec 19th, 2005
 

my question is Fact table is normalized or denormalized? ok

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sreenu

  • Dec 19th, 2005
 

hello karthik, i am asking is fact table is normalized or denormalized? ok

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bhargav

  • Dec 19th, 2005
 

hi

karthik

in every scheema fact table is in normalized form only.the fact table consits of composite keys  and measures

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Sridhar

  • Jan 13th, 2006
 

Fact tables are always in de-nomalized irrespective of whether it is a Snow Flake or Star Schema. Fact tables are nothing but OLAP tables and so they are denormalised.

Ravi

  • Jan 17th, 2006
 

What sridhar said is 100% right.

Ravi

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satish

  • Aug 9th, 2006
 

hi ravi,

In general

In Star Schema Fact table is normalized & Dimension tables are denormalized.

In Snow flake star shema Fact table is normalized & dimensional tables are also normalized. where we have to use more no of joins.

So Star schema is better way of representing the data.

bye

satish

siva

  • Aug 29th, 2007
 

Hello karthik

star schema : normalized

snowflake  :  denormalized

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venu adavelly

  • Sep 12th, 2007
 

Star Schema have normalized fact table, de-normalized dimensions, but in
Snowflake Schema contains de-normalized fact table normalized dimensions.

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