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By N.Gopinath AP/CSE. Two common multi-dimensional schemas are 1. Star schema: Consists of a fact...

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By N.Gopinath AP/CSE
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Page 1: By N.Gopinath AP/CSE. Two common multi-dimensional schemas are 1. Star schema: Consists of a fact table with a single table for each dimension 2. Snowflake.

ByN.Gopinath

AP/CSE

Page 2: By N.Gopinath AP/CSE. Two common multi-dimensional schemas are 1. Star schema: Consists of a fact table with a single table for each dimension 2. Snowflake.

• Two common multi-dimensional schemas are

1. Star schema:• Consists of a fact table with a single

table for each dimension2. Snowflake Schema:• It is a variation of star schema, in which

the dimensional tables from a star schema are organized into a hierarchy by normalizing them.

Page 3: By N.Gopinath AP/CSE. Two common multi-dimensional schemas are 1. Star schema: Consists of a fact table with a single table for each dimension 2. Snowflake.
Page 4: By N.Gopinath AP/CSE. Two common multi-dimensional schemas are 1. Star schema: Consists of a fact table with a single table for each dimension 2. Snowflake.
Page 5: By N.Gopinath AP/CSE. Two common multi-dimensional schemas are 1. Star schema: Consists of a fact table with a single table for each dimension 2. Snowflake.

Fact constellation is a set of tables that share some dimension tables. However, fact constellations limit the possible queries for the warehouse.

Page 6: By N.Gopinath AP/CSE. Two common multi-dimensional schemas are 1. Star schema: Consists of a fact table with a single table for each dimension 2. Snowflake.

Data warehouse also utilizes indexing to support high performance access.

A technique called bitmap indexing constructs a bit vector for each value in domain being indexed.

Indexing works very well for domains of low cardinality.

Page 7: By N.Gopinath AP/CSE. Two common multi-dimensional schemas are 1. Star schema: Consists of a fact table with a single table for each dimension 2. Snowflake.

Thank you…


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